{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "回归模型试图预测连续空间中的目标。回归计分可视化工具显示模型空间中的实例，以便更好地理解模型是如何进行预测的。我们目前已经实施了三种回归评估：\n",
    "\n",
    "+ 残差图Residuals Plot：绘制期望值与实际值之间的差\n",
    "+ 预测误差图Prediction Error Plot：在模型空间中绘制期望值与实际值\n",
    "+ alpha选择：视觉调整正则化超参数\n",
    "+ 库克距离Cook’s Distance：描述了单个样本对整个回归模型的影响程度\n",
    "\n",
    "\n",
    "Estimator score Visualizer包装Scikit Learn estimators并公开Estimator API，以便它们具有fit（）、predict（）和score（）方法，这些方法在幕后调用适当的估计器方法。Score可视化工具可以包装一个估计器，并作为管道或VisualPipeline中的最后一步传入。\n",
    "本文如果数据集下载不下来，查看下面地址，然后放入yellowbrick安装目录\\datasets\\fixtures文件夹:\n",
    "\n",
    "```\n",
    "{\n",
    "  \"bikeshare\": {\n",
    "    \"url\": \"https://s3.amazonaws.com/ddl-data-lake/yellowbrick/v1.0/bikeshare.zip\",\n",
    "    \"signature\": \"4ed07a929ccbe0171309129e6adda1c4390190385dd6001ba9eecc795a21eef2\"\n",
    "  },\n",
    "  \"hobbies\": {\n",
    "    \"url\": \"https://s3.amazonaws.com/ddl-data-lake/yellowbrick/v1.0/hobbies.zip\",\n",
    "    \"signature\": \"6114e32f46baddf049a18fb05bad3efa98f4e6a0fe87066c94071541cb1e906f\"\n",
    "  },\n",
    "  \"concrete\": {\n",
    "    \"url\": \"https://s3.amazonaws.com/ddl-data-lake/yellowbrick/v1.0/concrete.zip\",\n",
    "    \"signature\": \"5807af2f04e14e407f61e66a4f3daf910361a99bb5052809096b47d3cccdfc0a\"\n",
    "  },\n",
    "  \"credit\": {\n",
    "    \"url\": \"https://s3.amazonaws.com/ddl-data-lake/yellowbrick/v1.0/credit.zip\",\n",
    "    \"signature\": \"2c6f5821c4039d70e901cc079d1404f6f49c3d6815871231c40348a69ae26573\"\n",
    "  },\n",
    "  \"energy\": {\n",
    "    \"url\": \"https://s3.amazonaws.com/ddl-data-lake/yellowbrick/v1.0/energy.zip\",\n",
    "    \"signature\": \"174eca3cd81e888fc416c006de77dbe5f89d643b20319902a0362e2f1972a34e\"\n",
    "  },\n",
    "  \"game\": {\n",
    "    \"url\": \"https://s3.amazonaws.com/ddl-data-lake/yellowbrick/v1.0/game.zip\",\n",
    "    \"signature\": \"ce799d1c55fcf1985a02def4d85672ac86c022f8f7afefbe42b20364fba47d7a\"\n",
    "  },\n",
    "  \"mushroom\": {\n",
    "    \"url\": \"https://s3.amazonaws.com/ddl-data-lake/yellowbrick/v1.0/mushroom.zip\",\n",
    "    \"signature\": \"f79fdbc33b012dabd06a8f3cb3007d244b6aab22d41358b9aeda74417c91f300\"\n",
    "  },\n",
    "  \"occupancy\": {\n",
    "    \"url\": \"https://s3.amazonaws.com/ddl-data-lake/yellowbrick/v1.0/occupancy.zip\",\n",
    "    \"signature\": \"0b390387584586a05f45c7da610fdaaf8922c5954834f323ae349137394e6253\"\n",
    "  },\n",
    "  \"spam\": {\n",
    "    \"url\": \"https://s3.amazonaws.com/ddl-data-lake/yellowbrick/v1.0/spam.zip\",\n",
    "    \"signature\": \"000309ac2b61090a3001de3e262a5f5319708bb42791c62d15a08a2f9f7cb30a\"\n",
    "  },\n",
    "  \"walking\": {\n",
    "    \"url\": \"https://s3.amazonaws.com/ddl-data-lake/yellowbrick/v1.0/walking.zip\",\n",
    "    \"signature\": \"7a36615978bc3bb74a2e9d5de216815621bd37f6a42c65d3fc28b242b4d6e040\"\n",
    "  },\n",
    "  \"nfl\": {\n",
    "    \"url\": \"https://s3.amazonaws.com/ddl-data-lake/yellowbrick/v1.0/nfl.zip\",\n",
    "    \"signature\": \"4989c66818ea18217ee0fe3a59932b963bd65869928c14075a5c50366cb81e1f\"\n",
    "  }\n",
    "}\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "# 1 残差图Residuals Plot\n",
    "在回归模型的上下文中，残差是目标变量的观测值（y）与预测值（ŷ）之间的差，即预测的误差。残差图显示了垂直轴上的残差与水平轴上的因变量之间的差异，使您可以检测目标中可能会或多或少地产生误差的区域。\n",
    "\n",
    "\n",
    "|可视化器|ResidualsPlot|\n",
    "|-|-|\n",
    "|快速使用方法|residuals_plot()|\n",
    "|模型|回归|\n",
    "|工作流程|模型评估|"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# 多行输出\r\n",
    "from IPython.core.interactiveshell import InteractiveShell\r\n",
    "InteractiveShell.ast_node_interactivity = \"all\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "## 1.1 基础使用"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from sklearn.model_selection import train_test_split\r\n",
    "from sklearn.linear_model import Ridge\r\n",
    "from yellowbrick.datasets import load_concrete\r\n",
    "from yellowbrick.regressor import ResidualsPlot\r\n",
    "\r\n",
    "# Load a regression dataset\r\n",
    "X, y = load_concrete()\r\n",
    "\r\n",
    "# Create the train and test data\r\n",
    "# 数据分离\r\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)\r\n",
    "\r\n",
    "# Instantiate the linear model and visualizer\r\n",
    "# 初始化模型\r\n",
    "model = Ridge()\r\n",
    "# 残差可视化\r\n",
    "visualizer = ResidualsPlot(model)\r\n",
    "\r\n",
    "# Fit the training data to the visualizer\r\n",
    "visualizer.fit(X_train, y_train)  \r\n",
    "# Evaluate the model on the test data\r\n",
    "# 评价模型\r\n",
    "visualizer.score(X_test, y_test)  \r\n",
    "# Finalize and render the figure\r\n",
    "visualizer.show();                 "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "残差图的常见用途是分析回归器的误差方差。如果这些点围绕水平轴随机分散，则通常适用于数据的线性回归模型；否则，非线性模型更为合适。在上述情况下，我们在二维图中看到相对于目标的残差相当随机，均匀的分布。这似乎表明我们的线性模型运行良好。从直方图中我们还可以看到，我们的误差通常在零附近分布，这通常也表明模型拟合良好。\n",
    "\n",
    "请注意，如果不需要直方图，则可以使用hist=False标志将其关闭：\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "visualizer = ResidualsPlot(model, hist=False)\r\n",
    "visualizer.fit(X_train, y_train)\r\n",
    "visualizer.score(X_test, y_test)\r\n",
    "visualizer.show();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "## 1.2 快速方法\n",
    "使用关联的快速方法，可以在一行中实现与上述类似的功能residuals_plot。此方法将实例化ResidualsPlot可视化程序并将其适合于训练数据，然后将其在可选提供的测试数据（或未提供的训练数据）上评分"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/envs/python35-paddle120-env/lib/python3.7/site-packages/sklearn/ensemble/forest.py:248: FutureWarning: The default value of n_estimators will change from 10 in version 0.20 to 100 in 0.22.\n",
      "  \"10 in version 0.20 to 100 in 0.22.\", FutureWarning)\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from sklearn.ensemble import RandomForestRegressor\r\n",
    "from sklearn.model_selection import train_test_split as tts\r\n",
    "from yellowbrick.regressor import residuals_plot\r\n",
    "from yellowbrick.datasets import load_concrete\r\n",
    "\r\n",
    "# Load the dataset and split into train/test splits\r\n",
    "X, y = load_concrete()\r\n",
    "\r\n",
    "X_train, X_test, y_train, y_test = tts(X, y, test_size=0.2, shuffle=True)\r\n",
    "\r\n",
    "# Create the visualizer, fit, score, and show it\r\n",
    "viz = residuals_plot(RandomForestRegressor(), X_train, y_train, X_test, y_test);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "预测误差图显示了数据集的实际目标与我们的模型生成的预测值之间的关系。这使我们可以看到模型中有多少方差。数据科学家可以通过与预测完全匹配模型的45度线进行比较，使用此图来诊断回归模型。\n",
    "\n",
    "\n",
    "|可视化器|PredictionError|\n",
    "|-|-|\n",
    "|快速使用方法|prediction_error()|\n",
    "|模型|回归|\n",
    "|工作流程|模型评估|"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from sklearn.model_selection import train_test_split\r\n",
    "from sklearn.linear_model import Lasso\r\n",
    "from yellowbrick.datasets import load_concrete\r\n",
    "from yellowbrick.regressor import PredictionError\r\n",
    "\r\n",
    "# Load a regression dataset\r\n",
    "X, y = load_concrete()\r\n",
    "\r\n",
    "# Create the train and test data\r\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)\r\n",
    "\r\n",
    "# Instantiate the linear model and visualizer\r\n",
    "model = Lasso()\r\n",
    "visualizer = PredictionError(model)\r\n",
    "\r\n",
    "# Fit the training data to the visualizer\r\n",
    "visualizer.fit(X_train, y_train)  \r\n",
    "# Evaluate the model on the test data\r\n",
    "visualizer.score(X_test, y_test)  \r\n",
    "# Finalize and render the figure\r\n",
    "visualizer.show();                 "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "## 2.2 快速方法\n",
    "使用关联的快速方法可以实现相同的功能prediction_error。此方法将PredictionError使用关联的参数构建对象，将其拟合，然后（可选）立即显示可视化效果。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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DXpW2VOE2MYg0TiMaPVYipVcLjligKApTpkxBFEWys7MZOHAgAFu2bGH//v0899xzqKpKnz59AEhMTGTUqFGAkc0YSd+SOXPm8NRTTzF79my+/PJLbrnlls67oCggiUKbq3CbGLQlNT7YY+X9HUWdrt31asERqaZw0kknhbSPjqLrer25Z7CVgNVq5amnnqJfv37AieCvhklIkeQOjRo1irKyMr777jtGjBjR7fuyelWN4qo60hLsUVOVvy9kZ2eTm5tLampqRHEa7e2x0lZ6teCIBaNGjWLHjh3ouk5xcTGHDx8GYOLEiXzyySdcfvnlbNy4kcOHD3PppZc2eYymUuYbLps5cyYPPvhgi5XLYo2qaTy9Lp8VeUWom8p6feBXNAmmxkuSxCWXXIIgCBEFd7Wnx0p7MP96UWbgwIGMHDmS+fPn89RTT4WmIQsXLmT16tVcccUVPPvssy0mIY0ZM4b//Oc/vPjii6Flubm57Ny5kz/84Q8AXHDBBZSUlHD66ad37gV1gKBr0OXXOtU12NtQFIW33347ZFhvTz2NYI+VzpoSmhpHFJk7d26L68MFQXCqsnnz5tCy8BocTbU+WLNmTejzhg0bmDdvXoerVXcWXeka7E0oisLKlSvRNI2dO3d2KDW+MzEFRw/k7rvvprCwkGeffTbWQ2mWjroGOztkujsSLjS6IjW+I5iCowfy0EMPxXoIrdJe12DQLvJ9SYgL0lBodEVqfEfovX8Jk5gSdA1qDbxErbkGuypkujvR04QGmILDpBNZNHU0F43NIc4i4lVVEu0WLhqb06xrsDW7SG9NiMvPz+9RQgPMqYpJJxJ0DZ4eX8dgeWyr9oquDJnuTsyePZvhw4czduzYLhUaHbEjmYLDpNOxSWJED3xXhkzHmkOHDpGdnY3VakWSJMaNG9dl546GHcmcqph0G9prF+lpFBQU8MYbb/D222/HpDdONOxIpuAw6VYE7SKJdktEdpGeRnjCWlZWVqf1PWmOaNmRzKlKF/LJJ5+wZs0aamtrmTVrFtOnm8XcG9JVIdOxIBbVyBsSLTuSqXF0Am+88QZnnnkmF110EdOnT2fFihUATJ8+nYceeogHHniA//3vf+0+/rp16zj//PM599xzef7555vdrrq6mkWLFjFjxgxmzpzJli1bOHLkCFdeeSUXXHABF154IS+//HK9fZYtW8aFF17IrFmzuPXWW/F4YlOhq7NDprua7iA04IQdqSnaYkcyBUcnUFBQwMKFC3n//fd54okn+OMf/1hv/XPPPce8efPadWxVVXnwwQd54YUXWLVqFR9++CF79uxpctuHH36YH/3oR/z3v/9l5cqV5ObmIkkSd9xxBx999BFvvvkmr732Wmj/0tJS/vWvf/HOO+/w4Ycfoqoqq1atanRcj1+luKqu17pHo01ndo1vK5Hakfbt29ficb73gqMzHgJFURg6dCgAOTk5WK1WwMh4fOyxx5g6dSqjR7dvzv7dd98xePBgBg4ciM1m48ILL2T16tWNtqupqeGrr74KZeDabDb69OlDv379GDvWqCyemJjIsGHDKC0tDe2nqiputxu/34/b7Q6VAQiO/1itm5ve3tSphXB7G9nZ2YwYMSLmQiNIU3akC0b159KJg/H4VQ4fPsxll13W4jG+tzaOzgxtLigoYOjQoei6ziuvvMKSJUsAWL58ORs3bqSmpobdu3dz9dVX19vv8ssvb7JJ0+23387kyZMBQyvIysoKrcvMzOS7775rtE9RURGpqan87ne/Y9euXYwdO5a77rqL+Pj4etvk5+eHEqkyMzO57rrrOPvss7Hb7Zx55plMmTIltP3RWjfVbi91XtVscxAB4anxc+bMiTg1vrMJtyMdrXHzxpb9rN9/lJU7ikLPQWtV5b63giPokop2r48jR47gdDq54YYbKC0tRZZlbr75ZgCuuuoqrrrqKqDpLm4NK6R3BL/fz86dO7nnnnuYOHEiDz30EM8//zyLFy8OnX/RokXceeedJCYmAlBVVcXq1atZvXo1SUlJ3HLLLaxcuZI5c+ag6To17sZd8npjtms0EuwKCgrYsmULl1xyCTabrcuzmCO5BrtF4u1vD/D+NwolH79O34lnUjtsLO/vKOLS6fOB5rsixkRwyLJ8BfBbjPaP9wLfAcsBCTgCXKkoSqdZ5Toz5bugoIBTTz2Vf/3rX1RVVTFr1iy2bNnCKaec0uq+kWgcmZmZlJSUhNaVlpaSmZnZaJ+srCyysrJC2sSMGTNChlSfz8eiRYuYPXs25513XmifL774gpycHFJTUwE477zz2LJlC3PmzMGvavi1pquT9cSozqYerGhpoYcOHWL37t2h1PhoVZeLhLZcg9vn56133mHvipfwO6twFu1h1MI/IQoCm4uOc/qYPs2ep8sFhyzLaRhd6icBicADwKXAs4qi/FuW5T8A1wHPddYYOjO0WVEUxowZA0BycjKzZs1i7dq1EQmOSDSO8ePHc+DAAQoLC8nMzGTVqlU8/vjjjbbLyMggKyuLffv2MWzYMDZu3Ehubi66rnPXXXcxbNgwrr322nr79O/fn2+//RaXy4XD4WDjxo2hiEaLJGIRBXxNmIJ6UlRnSw9WNLTQgoIC1q5dG2rL2NX1NCK9hsLCQhbeshhlzWcAJAwexaA5Pw9Npapc3hbPEwvj6HTgE0VRahRFOaIoyg0Y7SDfD6zv9G710XJJNYWiKPUMnz/+8Y9Zu3Ztu4/XEIvFwr333sv111/PBRdcwMyZMxkxYkRo/c9//vOQsfOee+7hN7/5DbNnzyY/P58bb7yRvLw8Vq5cyaZNm5gzZw5z5swJjW/ixImcf/75XHLJJcyePRtN05g/fz5gaGNJDmuj8fS0qM7moiaf+GxHhwOjgi5XXddjYgiNJLjL7/fz17/+lTPOOIPP13yG5Ihn4JzrGbHgXhz9BoT2SY5ruTewEElx3Ggiy/LtwGggFegL3A+8rihKv8D6XGC5oiiTmztGXl7eEGB/w+W5ubkhD0ZrPLOhgFW7jjSqBn3hqGwWnjky4uv5vnGs1sUt//6CQzVe+tiMnimXyalIYuyNfq3hVTXu+NwoZdgQUcAocSg1fpf6NJ0/TskhI77531bDrvGnnHJKlxtCj9X5uGN9IbYmplXBa3Cobq677joqKyuZOnUqWef+jK9rpEbPwcyhKVw8vC/A0EmTJh1oeLxY2DgEjCbTlwCDgc+o36G+S7rV/2b6RGw2W5PVoLuiYExP7VZvtVp55bpzqfHpERsPu6p7e2sUV9WhbiojKa7xmN1+P1k2G/4mXMuJdgtnn/GDFq/18OHDoelJUlISp556alTHHgkev8rggrpGSYKq101SnD10Dc8++yySJHHeeefVm7qFPwe/OG0Y+Tt3NnuuWAiOUuALRVH8wF5ZlmsAvyzLcYqiuOiibvW9ObS5s7FbJJLiIxPQ3YmWsm/TExxMGdqPj/IPN9mTBAi1eGjqd3LhhReSm5vLmDFj+OabbzrvIlqgqb4qVQVbKHz/Rc44/yLsFqN96MyZoe6rzT4HrUUMx0Jw/A9YJsvynzCmKonAx8BPgFcC/++ybvXB0GaTyAjGJrSF8L4qsRTOrTUsWjR1NBZRqPf2nTqsHxow7+W1jYypRYWFZGdnY7PZkCQpFFgXS4LJgP/bqrDrvRep2rYRgNrdW1FVtdmkurY+B10uOBRFOSzL8tvApsCim4GvgH/JsvwL4CDwcnP7N4coini93oinKibtQ1XViO9xd+yr0lLDoqbevn9dv6tJL0VZ0UGSi7czYMAA5s+fj8XStkeps4oxi4JARtEWlKfvpaqyEkdcHHfcfju//OUvo5qJG6tu9X8H/t5g8bkdOabFYsHlclFXV4ckSd0iQq8lfD5fyC7TE9B1HVVVUVU14ockvK9KUlz3iDSNZIoafPs256XwlhWz6vMv+emEQfTv379ND2RnRixXV1dzxRVXsGHDBsDw6D3++OMMHjy4Q8dtil6Vq5KUlITNZuv2QgNg7969sR5CmxAEAZvNRlJSUkTbd/f6oZFk3wbjfcJxHztMxbZNuLw+5Aknt9nl2pnFmJOSkrBYLKSnp/P3v/+df//7350iNKAXhpy3VWWMJb15WtUb6oc2NKYGhQa6RuaIscw6f3qbhEZnRCxv3ryZ9PR0cnNzEQSBZ555hri4uFD0b2fRqzQOk+5DZwbZdRV2i8SUIRm4fH7clWUhoRE/aCQXzzgXh7Xll1TDzOumNJggQWEaKdXV1fzmN79h5syZLF68ONSsfMCAAZ0uNKAXahwm3YNwD0Y4PSXSNGiL+Hz/MUpq3NR5RazxqQzJyuCSmedxy1ljWthX58k1OxrZMX4xeWSHizHrus4HH3zAHXfcQUlJCRaLhdNOOw2/3x9x8GM0MAXH94RYtFQMejBW5BXgVdV6HozuTtAWIQBDUxPRdB136hRmjx/ErWe3XJH8DaWcLVV6k/kiLbmDW/u7FBUVcfvtt/Of//wHgFNPPZWlS5eGcqO6ElNw9HJi2VKxrX1VIqErBGDQFuEtK8ZZuIe+E85EtFiIt1nZcOAYHr/a7Lk9fpW8UieWuBNRwZqu41N1Vu8u4a2rpwJNu4Nboq6ujh//+MeUlZWRmJjIfffdx7XXXhuzpuOm4OjldFbdkbYQaV+VlohEAEZLqBx3eig+sB9n/pega7hLDxI/IBdo3bB73OmhyusnLQ50oKjSSaXLi0/VkUSBRz/dzj3nTWxzxHJ8fDw33ngjW7du5ZFHHqF///7tvj7o+L0yBUcvpr1W/O7YKb4lARhMiY+WVlVefAjf7q9B10gYLBPXf1hoXWu2iLQEO8k247EqqnRS5vQgYCTRCQJ8tqeUZEc+S6aNbVGYulwu/vznPyPLcqg+7eLFizusYURLAzUFRy+mrS7R7topvjUB6Nf0UI5JR7WqgoICPvrgfYakxFMUl0VS7viQyzUSW4TdYmQM51VqVLq8oYxNXdfp67BjEcVWXa9r1qzh17/+Nfv37yc9PZ1Zs2YRHx8flWlJtDRQ0x3bi2mrS7S7dopvyY1Z5nTzSUFJVALNwlsY3DzvQi6/aCZJDmubG0NdJqdy9vAsVE1H1UEUBdITHOSkGEK6Odfr8ePH+dWvfsXcuXPZv38/o0eP5pVXXqlXJ7YjRDMoz9Q4ejGtJXWFv/E6s5xiR2kpqzXRZqXG4yPO2vFAs4KCgnotDM4RBH71o7ZP2yRR4HfTx/N14XEqXV6skljvvjYU2rqu89Zbb3HXXXdRXl6O3W7nt7/9LQsXLoyqizWaQXmmxtHLibSlYjSDk6JNS71Apo/IIiMxOoFmF1xwARdddFG9MPL2NoayWyTOGZHVSGg0JbR9Ph9Lly6lvLycqVOnsn79epYsWYLVao1q+45oBuWZGkcvJ9K6I929U3xLWa2WsHl7kEhjIw4ePEhWVhZ2ux1RFKMaE9HSmH0+H263O5RftXTpUvbu3cvPfvYzBEHoFHtTWzTQ1jAFx/eE1uotRPNH1Rm0JABbekBbQlEUVq5cSf/+/bnsssuinufU3Jjz8vJYvHgxEyZM4NlnnwXgtNNO47TTTgvt21lu9Pbeq4aYgsMkRLR+VJ1JUwKw4QOaaLdQ6/Hj13SaKCEKnBAamqYxYMCAJlPjq91e9pTVMDw9iT6O9ickBsdcU1PDfQ8/zD/+8Q90XcfpdFJdXU2fPvXbEHSmvSlale9MwWESoqeXU7SIAm9u2d+qeh8uNJqqRu71+5n38jo2HyqjzqsSb5M4bVA6b109FVs7tZL//Oc/3HbbbRQXFyNJEgsXLuS2225r0mPSFZnFHa18ZwoOk0aE/6iCwWBWSaCwsq7Db9/OJBL1vjWhATDv5XWsDbzxLaKA16+xdm8p815ex4oFP27TmFRVZcGCBbz/vtH945RTTmHp0qWhfjVN0d3tTWAKDpNmCBrnPt1dwhcHjlHnM37EyQ4bpw/u2Ns3EtoavRqJel9WWtKq0Kh2e9l8qKzJ42w+VEa129smwSlJEsnJySQkJHD33Xdz/fXXt1oxrLvbm8AUHCbNEHx7by+poNrjQxQEdB1qPP52v30jISiwVu8u4WiNi35JcZwzIqtVb0JT6r2RXKbh9vs57vSFXAN2AAAgAElEQVSQnZ3NqFGjSEpKarZy156yGuq8KpJoXK8gnOjX4fKq7Cmr4ZSctBav4cCBAwChlhAPPPAAt912Gzk5ORHfh+5ubzIFh0kjgm9vo9G0P/TWEwTwaxp2i6Vdb99IWLp2J899UUCV24dP1dlf4WTX0So0XefXLaSzh6v3uq5TVFlHhdtILnNYBF7N28et08Zw7oyZlNd58apak2/uoakJ6Og4vWpIcFhEEbtFJM4mMTy9+dKJbrebJ554gqVLlzJkyBDWrVuHw+EgJSWFlJSUNt2H7m5vMgWHSSOCb2+vX0PVdMSwLm26bvyL9O3bFjx+lZe+2ku504MgCEgCaJpOudPDS1/tZeGPRrfYeT2o3h+urKPM6UYQBMTKEmyVhXyQGs+G/UfRA9cXXlyn0uULPZjLvtyLXRJx+dSQwPSpGrquMXVY/2YF5YYNG1iyZAl79uwBYMqUKfh8PhwOR4fuSXdt3xGLptPTgH8DOwKLtgGP0oXd6k1aJvj2rnR5DZU9bJ0QyPJ0WFt++7aH4qo6jlS5Gk0hBEGgpNpFcVUdQ9OaP+eiqaPxqxpPrMtHFwSkqlLsh74lwW6hcO9u8pP7My67L3aLRI3Hz183KLz45R5SHDbSEuxMGdqPz/eVMi67L9tLKqhx+1F1HUkQSHHYWH7FmY3OWVFRwX333ccrr7wCwMiRI7nxxhu55ppronpvuhux0jjWKopyafCLLMsv0YXd6k1aJvztneSwUOk6YeOwSqLRVHlQevS9K0LwP031MxZabQ4qiSJXnJrLe9uL8JUVU1uyA8FuIX7QSI4l9EfVwafq2C0CRZVOjtcZgjEjwUGtx8972wopqTaE04TsVPyahsurEmeTjGmbRyUpTIHQdZ3Zs2ezc+dObDYbS5YsYfHixWzfvj1696Sb0l1yVabRhd3qTVonmONy+qAMku1WRAEkEZLsFs7KzQxVsgrSUk5FsJNba/kW/fvE07+Po5HY0IHsJAf9+7Susqcl2EmoK8OZ/yWCrpMwWMY+ZCx+DayigFUS0HQ9lPLuUw0DKoBVEqj1+kP9Yy2iSJLDikUUm3SDCoLA4sWLOeOMM1i3bh2Lf/0bjrtVvGrj/rO9jVhpHGNkWX4fo2P9A0BC2NTkKJAdyUF6umTPy8uL9RBaZGoSnD6xD2Uj4nD6NDyqxpBkO4k2C9u+/RYwCvO+oZSTV+qkyusn2WYJdbAHTqxbfaDeuua620/v7+AdZx21Ph2/rmMRBBKtAtP7O9j+7dZWx3zo0CHU7etxu13E54yAfkPwuOoQdJU4UcJZW4tX03H7/KECOy5nLYdcKjU+FZdPY2vhcZLtEpnxFgTBEDQTc/rw7Td5vPfee6iqyvz58wEYMmQI99x7H3/78gB5H+w4cQ8KKlq8zp5OLATHbgxh8RYwDKNbffg42tWtvqfRXTq4t0STiVaONBaddsI1+uSaHWyp0rHEJZAWZ+y3pUpnoDMu9Nnl10hLTq63rrl8i5NO1hgUcMceq3WTkeiIyB0bpLS0lHPHDaE4LpuDiQOpcHlJjbeTkwGVbh9SQBA46lT8qkZ6goMaDWr9fkRRIinOQorDRqXLQ7lfYFx2X6blZnJWspdf33or3377LTabjcWLF4fK9xn3oCJ0D2pqalq9zu6Ox+Np8cUck96xwJuBr3tlWS4BftDV3epNWqe1SMyWgq5W7y4JfW64rqV8i466IWfMmMGQIUMYPXo0XlULHcMiCiEhWF7nITPRgcuv0j85jh2lVQiCYQTuG2djYEoCOSnx2CSJv19yMs8++QTnPfccmqaRk5PD448/HhIa3bmOSWfS5TYOWZavkGX5N4HPWUAm8BJGl3ro4m71Jk0TSbWolmp4HKt1c7TG1eS6SOp7NFUHozk7yoEDB/B4jOMFU+OFgLBLS7Bz3OnBr+ksmTaWt64+izevOovNSy7gV2fK2C0SPr+GJAqkJ9jJSUkIXWfpzq+YftZZoQzWX/7yl3zxxRece+6JNsfduY5JZxKLqcr7wGuyLM8BbMAvgS10sFu9SXSJJNGqqZyKYCuA9EQ7AgIuX2ODaLLDhsevtthmIJyWalPs3bOHFStWkJWVxc9+9rNQxayW9gnGRSyZNpYFp4/gp8vW4VXVekJS13WqN39M5eEiJkyYwNKlSznppJMaja0n5JV0BrGYqtQAs5tY1aFu9SbRJfyBCIZuB6tZBR+IcLetIAihVgBev0ZO33iGpyWhhlXt0oHCilrsVokrX10fcXGa5qZMZUUHSS7ejqZpDBw4sF49jUjrWfRx2JgxKpv3dxSh6zqquw5LXAI6cMWSO8ksK+DGG29stlZHR/JKumM1+UgxI0d7ALH4gdktElOH9asX/m2VBJIdVn45eWSjIjr/3LyHo7VurJJIv0QH/RIcVLq8pMTZ0N0iXlWlss6LDvRLcCAIQkTFaZqbMnnLiln1+Zf8dMIgJp9xer3ck7baHRZNHU3Z4UO89uTD+DSdU256kLOHBw2y57V6rxrmlcRZxBYLG3fXavJtwRQc3ZiY/8AEAQHDzRVM9hIAv6ZTXFUXEmQ3TRnF6t0lJMfZ6tXYlAIGxwcn92eQPIab3/my0dSlNSNiU1OmYNd4VVORJ5zcKGGtLfUsvF4vTz31FC8+/jher5fUtDT+PG0II4fnRnybGhp0Dyo7OOOHzXtTukOTrI5iCo5uTCx/YB6/yrq9pQzqmxiyW1gkgeKqOpauy2fl9kIyEh1My83k0omDqXR5m31QXf547JLU4jbNFadpaEPwVpeHusZnjhjLrPOnNwpRj9TusGnTJpYsWYKiKABcccUVPPjgg/Tt27ftN4wTBt0jzZUdo/d4YXqGXvQ9JJo9MNpDuLfAEFwixVV1lDk9uHwaYthU441v9rdYPTvZLrW7wnbDCufWxBTisgYRP2gkF884F4e18buvparoQbvDnXfeyQUXXICiKOTm5rJy5Ur+8pe/tFtoREpbvDDRrHAebUyNo5vSFeXjWqLhWzs8TNsqCVgDb1VREFh/4BhThvYLdVMLEnxQbZK7Q0bERVNHo+s6a/cdpbzOw4CTTmdabia3nNV8RfLW6lmkp6djtVpZtGgRv/71rzucxRopkWhDMZ+iRoApOLoR4UbQWLv5Gj7oRk6HjoDRyjD84S+v83DZyUOxiEKTD+rWLVuA9hen2btnD/0Ob+Vf8y/BqQoRGYkb2h3clWUUHTwQevAWLlzIhRdeiCzLHblNbSYSAfrkmh3d3gZiCo5uQHNvmKm5mXwYw/Jx4Q+62+/BYRVJsllDrQyDpMbb6ZfkaDXisz1Rodvzd/Hm2+/gkET2KLvaHKZvEeCDN5bz8MMPY7PZ2LRpE+np6dhstk4VGi15wloSoD3FBmIKjm5Ac0bQWWMGcNHYnJiVj2v4oL/69V4+2lVczxjZUJBFUngmkm1UTePe1/7Lqg8/oM7jI2vkWOKq7ZykaRGr69u3b2fx4sV88803AFxw4YUUVzpJSunbaQ+fqmm8mn+cvVvXNjvNaEmAltbUxXSKGimm4IgxLb1h1u07yltXnxXz8nHBB/3Ws8dikcQuEWT3vvZf3l2xAkHXSR46CsugMXyw8zCCILSqrtfV1fHYY4/xzDPPoKoq2dnZ/OjqmzmSNpKbPtpJWsLeTrMZPL0un3VF1ST36dPqNKMpARrrKWqkmIIjxkRqBO0Ob5muqoP5zbYdrFy5EgL1NJJyxyMEYkoiUdcXLFjAxx9/jCAI3HDDDaRMncvH+ysQPf5OtRlEY5rREyqcg+mOjTnRbATcVbS3EXNrqJrGk2t28MsXPqCo0smxpAFUpg6rt00kiWO33HIL48aN4+OPP+aBhx5m45HaLnFrRyvhLdJG4bHE1DhiTE95w3QFQVtP3IiTsPrsqClZHK8zChcP7GtkrTYUprqu8+abb7Jt2zYefvhhAE4//XTWrFmDKBqxJ11lMwi+BI646uot13SdeKuFRHtkj1t3r3AOpsbRLegub5hYBhwV7NnLp7sKEQUBSRTpmzPECHkXBCrcXjRdbyRM9+3bx9y5c7npppt47rnnQkZQMNLroWs1uoaBZ7quU1jhZHtJJbvLarjy1fU8uWYHqhZZacHO0uyigalxdANi/YZpT8BRNBPvCgoKWP7mv9m3u5LMH5yNIFlCdTGC2bY2SWTGqP4smjoan8/HM888w2OPPYbb7SY1NZXf//73nHzyyY2OHQ2Nri3XumjqaAqLDrPXY2H7kQqq3T76xht1PrpjPEZ7MQVHNyJWPTTakhMT7ajGgoICVqxYgUMSScvuD6LxYArAwJQEBiQblbj+fc1U+jhsfP311yxevJidO3cCMG/ePB566CHS09ObPUdzcRO/mDyyXrJeQ9pzrZIocsXoNEaMHd9knY/uFo/RXkzB8T2nrZ6AaCbeBYWGpmlMPuN04sgwXK4NtpsxKjvUimH58uXs3LmTIUOG8Pjjj3P22We3ep6GGl1KnJW/f1HAz5Z/3qJACL9WqyRy3OlhxfbCiK611uPH6fV1+3iM9mIKju85bcmJiWZUY7jQCDaAnqrrCELjsPWrJpwoev/AAw/Qv39/br75ZuLj2/bgBTW6SEK6g9cqAIUVzlA7SaskcLzOwy8mjyTeZm32XD0lHqO9mMbR7znNGQ8NT4C1nicgWu7GI0eONBIaQsAoGl4X9OnzZba+9CgzZ8zA7XYDkJKSwu23395moREk0qzj4LUWBdpJapoeaklZVFnHo5/uaOrwISLJ0O3JmILje04jTwBQWOlk+5EKdh+rqucJiJaHIisri3HjxtUTGuFYRYH/vvMGU8+czAcffEBJSQnbtm3r0HUGOe70cKzWjcevNnqow4VfWoKdlDgbFW5vaHw6oAW62X1deLxV71N38ZZ1BuZUxaSe8XD7kUqqPT76xtnJSYlvpMZ3xEPh9vkpr/OSlmBn5syZAI2ERn5+Prfcspivv/4KMNodPProo+Tk5HT4OlVN49W8few7XovLp2KziPR12MhJiUcIq6UKhkA9dWAq6/cdRRQFPH4Nv6ah62C3iOSXVnG0xsXAvomNzhPsXJeWYO/28Rjtpc2CQ5bluYqivNvRE8uyHAdsB34PrMZsOh0zglMEo+L3Wryq1qwnoD2p8aqmc9crH/HJ5xuQRv6QjJQkpgzJ4LJThtIvKS70MP3lL3/hgd//Hs3vx5KYwvBLFnDqxXPIDvQw6ShL1+Xz/MYCnF4/Hr+G26/i9Phw+/0MTk1kWu6Aeg/2b388jne+PcSBCic+VUMQDG3DKolUe3y88c1+bjtnfNh1Gl6YFXlFqJvKmqys3ltoVXDIspwM/ElRlBsDi66XZfk64CZFUQ514Nx3A+WBzw9iNp2OOYYnwN+qofSmKaO4ePwgEIx+r629Rf+2bhsbN25E0HWS+haR7+7PFweO8dzG3YzPTgk9XFsqVDS/n/QfTif73J9hiUuIOLGtNTx+lWWb93C8zotVEtF0Y5kfOFztpjLQ8e1XU2RsgYrmkihy8fhB/HXDLiyiJVR3VdeNmiTrDxxjUViLh6AXxuXXSIrrnnU0okUkNo4NwF+DXxRFuQD4F7BaluU7ZFlus+4ly/IoYAywKrBoGmbT6ZjTmg0jJc7Kk2t2MO/ltVz56noWv/cVf12/q8VIyO35u/ji83WhBtDlidkhY2NNVSWFWzfx/o4inlizk7L+4xm18E8MvOh6LHEnGiNFI6ekuLqO4mp3WMFlrV5za1EQWLe3lHkvrwvlzMx7eS3/3VWM26/h01RUTUcUBdITHOSkxNezicS61GNXE8lU5Q1gMYYWAICiKG/Jsvwf4GHgG1mWf6Uoyvo2nPdxYCFwdeC72XS6m5Br97PuWHUjG8bEnD7c/dZnrCs6se6Iq45Xj5VTWHSYK0an1TtOrdfP17v2s33zetx+lcSsYWgZgymrdqFpOsLePLSN73LA62LQtffyrrMWp1/FkZBKTU1NvWOVV+l8tvErMuKbd3+2hFfVUMrd+NUTrlFVq28Y9asqkiiyYW8Ji5Z/zOYjTsRAlXa7KODXNBKtOtkJEqKgUVtbS5xF5KCygyOSyLE6HwePHscWiAMJv4aOjr870qrgUBTlIVmW601gZVkeB0wG+mD0ev1IluU3gMWKotQ1cZjwfa8CNiqKsr+ZCkxm0+kYctLJWr0eq+FRlj9b/jnJffo02mevx8K4iSdht0h4/X7mvbyOjVu341G+wiKA3m8IQ8aeil8H/fA+pM9fh0Ij8jNhyGgSk/qgO+LJtlnwN3igARLtFs4+4wdtbm4UHvl5rNaNjoBf07FaRHQ0Y9qB8YOzWYzO9F5VY0eNUO8601WRMqcHLwJJSUmIgcbVF43NCbVB8PhVBhfUUevxU1NTQ1JSUpvG392IStNpRVHyg59lWa7EMGCuBz7F6Dx/EEMreRu4oJXDXQgMk2V5FpADeIBas+l096C5vJmWskzLnG52lFQyNiuF+S+vY+3eUoSKUkR0tMxc6jJy2XaknKwDmxA/+Tf4vWCLI/Hs+Qyfcj6CIJBotzBlSAYf7Spuk8cmKBxW7y7haI2Lfklxoe724ZGfcVYLmYkODlfX4VeNqVVIaIhCyLtjt0p4/BrxthOz+GDeTHmdlzqvj6w+8Y0MwuE5MeH0lriNhrTHHTtCUZRjTSx/Qpbl61vbWVGU+cHPsizfDxzA0F5+AryC2XS6W9Awb6apSEhdN4Kharw+Fr7zJX3jrXy+9ygWUYBB4yApHfpmYdc01M//zZEd64wdh0+izzmXMySnP0Lg7R18ENtSYczjV3nwv1t55Zt9OL0qfg32VzjZdbQKr1/li4NlISGkAwggBVyrEqACdknEbjGEhKbrTB6UgSgK9a4zmDczMqMPf5n7w2YzVoPjXJFXgFdVu7zUY1fSZsHRjNAIckk7x3EfZtPpbk1TWaZFlXUcc7rJSHQQZ5UoPnQIl0vHZnfgsEqQGmaqGn82Oc4iTv7p9XwtZFNS42b7kQqy+sRx7Q9yQ3kikcQ9qJrG0nX5/HPTHpRj1fU0BxGJcqeHf361l7R4Y1xg9Kw95vRgFUVEq8iI9ET2l9fi13Q0HeKsIqcNSuetq6fy7HqlyViVc0ZkMTQtqdF4ggTHf3p8HYPlsb0qbqMhUQ0AU4ItsSLf/v6wr2bT6S6mranx4TEcZU43NV4fGYkOclIScB87jGvnJuxeCd+IH6If3gN7v4EfXwVAXEY2lz3yAv+3u5QsQaBfkgOfqiOJhGpwBGktS/jpdfn8bYPCsYBHI2ir8Go6gl/DYZUoq3UzMCUBTdM5VOmkqLIOTdcRBLCIRtLahP6pOCwS982YwJjMlFAiXXvbOASxSWKvi9toiBk5+j2kvanx4RrBjpJKFr7zJXFWKdTLVUTHkZCIsGY5HNhq7DRkPPrgCZyak8bmwvLQW9xIMDM+B4PLgFYFmcevsnp3CVVuH+F29KDw8Gkadl1EFEXOGJLB69/sp6zWQ9DmqmqGR+Xb4koS7Bb62C0M6JMQEhoNr7O3RXxGCzNX5XtI0GhY26B479Pr8lvfGUMjGJuVQkaiPSQ0dE1F9bhg7etYD2wFiw3tjLnYRpzMKf0S+MtPftAoCU7TdTx+jWO1Hv74yXfMe3lt6F9zlbKOOz0crXHjU3VEwWiGHe6H0XXQgOwkB7eeNZo4i4TVIiIIhISHKAqouo6q6VS7fbyxZX+z19ldK3DFGlPj+J7RWqDSgtNHUOvxt/qWtVskxtndvLttI6qzmtoD+bhLjVoVuSefxrLnnsYTn8rw9CR279hGdp+EkHFVB4oqnVS6jFR1Vdc4WlPHoNSkVmt8pCXYyUiyk3+0Cq96Iogr+H9RgPR4G9ecNhyXTyM5zkZ6ooP9x2sornYR1FJ03RBc6QkO1u8/Wi8C1KR1TI3je0ZzqfG6rrP9SAU/Xbau1bc+QElJCX0Ob0NOT0JUvbhLC7EmJnPJrfex8X8fMnbkCE7JSQtNAcKzcIsqnZQ5PYEgLKOWaLnLR1GlM3T85iIu7RYJqyiiBhLOREFADMhAERie3odfTRnF4qmjSUuwkxpv43BlHTUeP6pOSNNQdR2/pqO3cE9MmsfUOL5nNFdgpqiyjmq3D6+qRlTZy263c9JJJ/HDH9qY9MPTeOTRx1i08FdkZTQu4RfMFv3F5JH4NZ0n1u4MpKcLJNusHK8zmllXurwMSI4PaUNNVcoKpsMPSI6npNqNy6+GvCp2i8jlk4aEbDVBw+sxpxFqLmJMY8AwkNoDVb0cktjjC+t0Nabg+J7RlFtV03Uq3F76xtubzYoNqvGVlZU8+OCDfPDBB2zcuJG0tDQEQeAPD9zX6FxNZYuePCCVIX0TkEQx1PG+xluJpun4NKOxddBo2lSNj+NOD+V1Xgb1TQQdjta6EATBCA8XBFbtLCbeamHJtLEBIQMZiQ4qXN560xkITG90HT3iWGWTIOZUpYsJtiDwqpGVyO8MGhaYsUkiSXZrKEIynOBbX9d1nnvuOSZOnMiyZcuorq5m06ZNjepphBOeLRrUYj7bU0JNIANXDDzwfR02dF3HKgpYJeN4fk3j5AGpjY4Z1Jg0XafS48MiSUiiiCAIWEUBu0UMTXEMIeNhYEoCI9L7EG+VcEgiYqCSlwCkJzhIcVjNqUobMTWOLqKhC1Tyubm4Lr5T+pe2RkN3Y6LdwpWvrm+2Pqar4hgX/b+FbNiwAYAxY8bwwgsvMGrUqEbbBx/YRLulSSOsRRQRdEMwWALXnZMSj4ZOnEXCp2pUubzoAvyfUsyWw+X1XMVBjenf3x404kDCtIeUOBuiIISEXfi0zG4RcVglVE1H1w1BMy47BYsokmi3mFOVNmIKji6iYXXwGpcW81oN4YFWzVX2Sjv8HVPPvBKXy4XNZuPaa6/loYceQpLqeyAaCsYEm4XdZTUMSW1cISs5zsbUof34svA4tV4f6QkOfnWmzC8mj+TRT7fz2Z7SkFBpytayaOpo/KrG/vJ83H4NqyiQEmcLaUzBKU7DaVlKnI2yYGnAeDsWUey1uSSdjSk4miGaDYeiWR08GjR1bQ2jJZMdNk4dmMbw1ApWuFyMHDmS2267jblz59abngSP9WrePj7KPxwSjF5Vo8ZjeEpSwi5N1XXKnG6+LiqnxuMnyW5jytB+hjDQdLYcrggJjSAN75MkikblLUHgvW2F2C1iPXtNuCAIv65+iQ7skoguQIrDKMTcW3NJOhtTcDQg2g2HoOUWBOGZpZ0tPFq7tiXTxnLVSTksWvoSVQPGs2pDHr7dX3PKeXP43Q1X8uOzzw4JjYYp6/vLa0N2EgFCtouKOg99kqyh2I3iqjpUTed4nZe+DhsOi8hH+YexiALzTx4auk+aruNTNaySWG/6Ee5huXXaGCxi43YK4YKgqSjQ4N/EjAhtP6bgaEA0Gw4FaS6ztLDCGcoszUjsuIBqjdYaDH366adc/6ubqSw9wvBr70ZXfXh9fioHjSFPS2d0tSv0sAWPBeBXNVxeFY/fiK3ITIrDKgn0T47D41eRBDhYXku124cgQJxVQtMMzQNgYN+EUPBZaryNXaXV9fqY9HXYGJXZp5Edoi2h4Q3zX3p7LklnYwqOMDprStGUC7S0zk+N3xfKLO3s+pQtNRg6WnaMHa89xbtvvw2AI2sQkiOexP5DsaVkcMySwpOf72LFjsNkJNqZMrQf6/aWcLiyjgq30dvVHQjUqvP6OeZ0hyps2SQRMc6CVRQZnpHErtJqgrc32FB6gG6U4av1+ENxF6IghPqYHHO6GSMkRywUTDofU3CE0ZauZm2lYWapy6+RkRhXzwXamTaP4LUdrXFT5nQbsQ/oqDs3UbLxHd51O7Hb7SScMp3+Z1+CZotHB8qsfTnudKMHXKe1Hj/vbStEOVqFHui8ZhEF9EBUpoAR8OVXdXR0HFYRl1+npMaNGgj68ms6um7kmfhUY0qSlmAn0W4JxV1Uurz4NMNFmxZnDxUXNqcW3QMzjiOMaDUcaorwLmV/mXsa/ROtDAzYA8Ipc3rYUVIZ9eK2TTUY4rtP4bN/IbidJA8fzx+f+Tse0cqO9Z+w/XAZ249UcKTGBYEYiWCMhVUSqfOFTbsC/w1mqPpVDUHQjfqbupFUZrWIVLqNICyn1x/6p2oaoigwLTeTWo8/FHcxNiuFsZkpjM1KYWBKAhUuMyy8O2EKjjC6om1fMLM0xV5f2Qt2UNt3vIaF72xuNVekPec9dWAqPn/Y8UadAX2zEc+5mqpJl3Dr39+m3Omm1tGXOr+G06vi9qt4/CrJDis+VUML5HqAEb6tA26fEaEZiswE4q0WHFYJv25kpfZ12HB6fPhUI35DCExDdHRS42wsCuSWBIWzYWM64S3pDf1WexOm4GhAV7Tts1skJmUm1BNQRZVOjtW6SbJZibNa2pzqHgnTUzzEf/ZPRM2PBljiEpB+djdaxmDUPXl4/H7UfkPx95fRMAr36rpRv6LC5WPbkUq2l1RSUlNHH7sVqyhQ4/HhCctSlQSjJJ9XNRLIpICton9yHJZAmLlVEunjsDIwJZ5Tc9IMLSUgjE4e0Bd/A2Fpxlp0P0wbRwO6qojLZXIqA51xAZuHhxqPj4xAv44g0bJ5VFdX89BDD/Hiiy+i6zqZQ2TSJs9CEgV27tqFticPVVXxB4RG0HqZYBVx+TV8mk6Nx4euE+p+luywhTq+CRgPd1B42ETBaHakaUiiwP4qlWSfk7QEO0NSE+u5WQGOO9388ZNtbDlcTpnTQ3UgcjTFYSUtwWHGWnRDTMHRDK1Z6jsaICaJQoNqWpuJszb+czSXIRrpuVetWsVvf/tbjhw5AqJI2uRZiOOmUun2YHPXoO7OQ0TH328oan+5XoNlr6qh6Y3VUkEQcPr8pMXZcHr99aYpqg5aQNsIahi6rhqVxgNTj4ZjrnT7+GxPCRZRxGGRcCTF4dc0zh6exe+mjzc1jW6IKTjaSLQDxKbFXx4AACAASURBVE5U03I0mysSnNu35dzFxcXccccdfPjhhwDE5+QycM4NxGcPBoxckR+NG8jqimJ2V9Shp+cGNAfCup0ZAsFuMXJEgp4QXQen10dmZhxHnW68/mA1LgFdNzwmDqvIpJxUVE3HXeckuU8ipbWuejkqwXEIOo2iRS2iyJbD5Zh0T0wbRxvpaNm9pojUKNuWc2/YsIEPP/yQhIQEhl50HYOvewBH1iAA9MDDu+1IJeeccw7+rJFYJAlBEBqV4pMEY3xGNGhAqAgnusyLiIH9jO/BzwJCSLsITklSHFbOHp5Vz3509vBM+sTZaIrwFosm3Ysu1zhkWY4HlgGZgAOjW/239IBu9Z2Zc9JaZe1Izu2qrSElJQWASy+9lP3791M6YCLLdlaiHa3GKgkk1h0nsfwAqROnUK5auea04azYUcTBCmdIWwgWxRmYEo+ISElNXcjuAYCukxZ42CVRwIpo9GLVCfUokUQRn6rVux9pCQ5+N93o7h4e/r3lcEWr2pZJ9yIWGsds4GtFUc4C5gFPcKJb/Y+APYT1qe1OtFRirqNvx/A4jzevOou3rj6LJdPGhqYgLZ27rKqG+x74PRMmTKCgoAAw3vzWH17I1xU6omhoC/7jRyjftpHjR4/iLi0kNd5Ov6Q4BiQbNoXgFEUH3H6NKpePERmJpMbbAwV+jZiM1AQ7S84ew0/GDyLOJmGzGF6SnJR4Jg1MI7uPEXJudIXX8Wo6fk0LaU/hRYC7wgVuEn26XONQFOXNsK8DgSKMbvU3BpZ9APwGeK5rR9Y6zZXdg+i9HYMPVbDgT/CYHlUlJc6Gy1c/MKxm3w4Ov/8C+WVHAPjss88YOXJkSEOxiCIpDivFB/cj7PsGNJ2K9MHY47PI1HUuX/456/aV4m0i3qzG46PC7WNcdgp+TedYrYuMxBMtFiVRxK/rvPPdIRJsVqODG0YeyOjMZPaV1XCkxo3f7ydHsgZiQLRG9piO9jEx6XoEvYGk7ypkWf4Co3fsLOATRVH6BZbnAssVRZnc3L55eXlDgKZr2ncyr+Yfr9exHYy349ScPo06trcHVdN5Qyknr9RJpcdPrc8Is0q0itT6dLyqRla8Fc3t5Nhnb1O7zSiuM3jwYBYvXsy4ceMAOFbn4471hdhEkcOFh6jK/xp0w3ui9ZeJs4kkWkVS7BaUCg9N/QoEYGyagxS7hQcn98fl10m2S9gkMTTOr0tq2Vvlxqsa7RSHJds4NSsRTddZV1SNphv1PYONmlu6T15Vo8qjhs5h0i0YOmnSpAMNF8bMq6IoymRZlk/C6BcbPnHv1t3qm+vm3lavSnPd6p9cs4MtVTqWuARcHicVXg/oOpLFyuCMBAoraqk8qFD+/t/QXTUgWRh0zk+4YsEv+H/nTAiNIdg9/WjhAdx7tmCTBMjMxZozCkkU8agax90a1V5fs0IDIC4hAU0UGDFmfD2XcHCc1vhERsUnBnqkqMweN5BFZ41h3str6ZucDFCve3t4Z/veSnN/255EVLrVRxNZlicBRxVFKVQUZassyxagpqd0q+/MALFwA6im61S6jOrfhGWRDuqbSFF1GvjcJAwZzaA5P8eR0Z9VBaVI1vxQZm3QdvDS1i/RVA2yhqINkEPHM1LgdSxS03Jax7CLiILQaBrWlKE22BF+/YFjXHqy0dneKomhMPUgHU0WNOkexELjmAoMBhbLspwJJGJ0p+9R3erbmsodSdBWeHaukTVqxEfomopPycObPh1RFCkVk8i59n7SBw5FCpS/86kaq3eX1PPsLJo6GpfXx+/dVrxJGeDTEAFBUFEDz7Lb1zgXJuhydVgkrIEEtPAxt5ZFrP7/9s48Os7qTtPPt9QuqbRLliVZNsafF2HHMVi2LDsG3MHpZoAkxCRh0mTIDJwZEnrJnPQJ6RB66DQDNE1yukl30kA3SRg6ATrYBAg7toGw2GHxRsnYxqtsWWtJtX/L/PFVlau02CpbUknl+5zjY6lKKt2rc+rVvb/tNSz6onFOJB3XJMugyghRX+o9q1jQeE5jE4wP+RCOfwEe0jRtK+ABbgG2UaBu9aMVba3yDb8gZAZf7ayEhN5xAGvLY8hdh/nIMgjOvhjTgj0UoX5ykhKPA5BIGBaqDHe9tIPr5xZRN2MGPp+Pdw73IJXVoJikUyZG8gQgYadTDfNUuXjqlKFIMKvMxzXNDcOClGcKEv9mxyFiCQPDtIcJ66Y96czE4pZV2pjf/BMxjU0wPuQjqxIBvjrCUwXpVj/aRLHDfonll2R/bebAHzMWxXj9cawPX0WyLMyiciKOorT/qQToFvSEE3aZdrKc+7nfb+eDTXu4ctkCrrp2A28f6sLtUJMt7FZWPEPGnkSWunDIElw0o4zqIjctsyr4zmXNeJ2OYXsaaTAR2EHitqYqXj/QSUNZEZKUsnkEVZHxqAo3t847598d5G/As8BGlJxPIENjAfaVwp66tf1EKD2YJvMofuuaBezd9iaP/9M9WMFukCT0iy4jtGQ9OE4d8TMFIGEYtitaqJuBQx9yQIGGWU0cCsYIx4201aEs2yXhaef25AtJgFORqCl286/XrRzT/NPRUqjXLpnFxl1HcKkKDaU+Zvq99AYHKCspRjdN+iKJEcXoTL+7FPka8CzIRgjHBJKKBThVJctk2aFIOLHoCIb4zYeHs47iNZ17eOLe7wOgVDdirb0evXQmZNRvZFoZgt1YFu86Rv+hD4gpMlVzF7Do4hUUux14HAq9qSArdp/JUFJt7T6nY8xDk0cLEsd0I+saI0sSzmQ6Npf4xkROYxOcO0I4xpnM00Pq354T/XSFYul+D8O0CJkG33ryXQbjetbw4B7PLGoumE9//WKi81cjyQoOQEoY6VOGJNm1+akApyPYifvQB1iWSaSqiUSdRmWRG5eqsGRmGa+0H0+eNrIFB1L9J3bwwxwxMXt6hgaJT3eNyaUSdDKK7QRnjxCOcWK0QF5rUxVvHujMKk6xLLuga9uRbmYxwCfPPor+mevRnT4cikTF5/83ZlRHStpEpoKYqWE3KZNlACkSxPnJ+yBZUHsB1M9HzvhpT9ywhnl3baQnHB9W1g0kry12nGMwmqBzIEpD2XAryFwYeo3xqHLOw5DGS4AEE4Nyxx135HsNOdPR0VEK/Hl1dTWqOrL2xXSDzoEoTlUe1rI9HgSjcXYd78PnVHGpCj/evJtNu44ksxsyccPko84gdSUePuoMkjAtdBNURaLC66KYON1vPEPP0z/D6D6GlYgjz2rGsiAYS2BaSdGQTs351JOTtlLpUkUCf3ERiqljFpWjNi6g3Oum2OVg/YI6yjwuXKqKIkFfNE6p20lcN9CtUwM0FElCliU7m4Jto7hqdvU5/W5kSWJlUzVfWNzInyys5xJfjC+t+tSweMWZWN5YSV8kzrFghMF4Ar/HyRVaHbeuWZDza00mHR0d1NXV5XsZ54RhGHR2dgL8uK6urm/o8wV34pjoFF5c19nwyBbePtRFOG7gdSpcXG+XUI8UyNt+pIeFtaWE4np68lX44Ed88p8/Re45bn/h/Fa45Mr09zlVBRkodjvojyYIxXQMy0KRZUqdChuWNnHjJXO4/fkdRBIGRm0rccPk5GCM/micnnCMbz35DpdfWMstbRomEIwkOBaMEjNM26EdO1gqYZ+AVFmm3Ofm9QOd3DpO08RT15iOsywfn6xpbILcKTjhmOgU3oZHtrA5Ge1XZYm4brJlv91M9qkR3NX7o3Euv7CWzfs6URIRjvz2/9G97RUA3JV1hFduQKk/laK0gDKPE8O0qC5yI1mQ0A1kSQZJotTrYvuO3fRte5nVn7mC3+3rRpFluoIRusN2eXqlz00kYbBp1xE27ztBfzRBdbGHyiI3ccPkaF+IY8EokmVhSXYrfG2xbdUwFQOPwjdl6lFQVTRnSuGdq+VAMBrn7UNdw15fkW27gKFDdsEO5H3nsmauWlSP1NtB97ZXkBSVJeu/yAfvvEHDwiUosoSJHceo9LmoT9oD/JcFMxlM6EiyjKrIVPpcVCb66N/5Njv3H6K1JM5Vi+rxOBR6wvHk92fPLX37UFfW78GtKsyuKKbc62RpfTkX11dycUMljWVFSIjAo2BsFNSJY6JTeB93DRCOG+n28RSpz0IxHX/GNCvTsmip8eJ1OtJH7h9VGHzus+tIRCNUlfq5sWUuT+08jGHaZkWpPpVL59Zw3dLZPL3nWDLrIhHvOkbvjrfAMpFmXMichUtYXerjmosaue6RzfhcjixRSyStGROGhUvN7ivxOdVkf4mStV4ReBSMhYI6cUykoRLA3MpivE77TWVB1pBev9vJFxc3psfi+RwSNfvf5J//55fYsmULYB+5/+ovbmXxooXp17x1zQKuaW6gwudEN80sO4YKn4uqIhcuVc4SDd8sjYbmZVQWuQF7/sUMv3fYScihyHicStpICUh3sc6v9vP55oYJtYEQFC4FdeKY6BReidvJ8sZKXgwcw7BID+9VJGibU8d3/2gxMd3gjXf/wJ3f+ytef/99AF588UXWrFkz4mueLgCoyLD2ghp+/drb9O98Oy0avjnNXDq3Nms/S2eW8erHJ4ZlkFoaK+mPJrAsiyNJr9eEbtJQ6kVVannsa6vpiyRE4FGQEwUlHDCx06QM08QyTQzTQk8eNWQLij0O2mZXEQ6Hueeee3jggQcwDIOZM2dy7733sn79+jO+9mgBwFvXLGD/B9vYLINZcwHV8z/FunkzuHXNgqwM0mh+JLe0aTzweoCH3vmYzlAUpyJTXeymqtgzLGgsulAFY6XghGMiU3j/8Ooufn+omyKXA9M0STWclntd/O6Nd3n0L/+UQ4cOIkkSN998M7fddlt6gM25MHvxMnaHZIKusnRdR0w3uOeVnelTxun8SP5X23xe3nucUrcrHUcBu0bktX0nuLl1Hj99s110oQrGTMEJR4rxTuHFdIOX9h4nYdit4rIspwNEfZE45b5iBkMhmpubuf/++1m2bFnW3NBM8YrpBifDidO6r+/fv5/q6mr+ddtBnt59FLm0hhIgHNd54I0AD771MccHosiy7ctaX+pNOscP9yPpDsXoi8RHDRrf88pONu/rFF2ogjFTsMIx3nQnbRodimSbJVsW7NsOTUtIqA78pWX87KmnWDDvQmRF4f7Xdg37C566Nry27wQHO7uZ1R4e8S97e3s7Tz31FCX+Ul5hVla85khfmJ5QDFmWMSwTTImuUBQgXSo+NIN0ur4Pv9vJtsM9ogtVkBPiHDoGYknH9nKvizK3E7P3ONamH8OLD8MfnkeVYN28WhYvWojD4RjVOGnDI1vSjztleURDpZRomKZJ5cxGeqKnak9My6I3GkeS7OE7qUColBwtmOpFGZpBOp0FwcUNFfRF4iPuWxgiCUZDCMdpMEyT+1/bxYZHNvO1R19n/8leurduhMf/DulYO5bbh15SxdL6cm5p04Dhc0Nj+qmZm6lirJTXiGlZWcVp7e3tPPmfv6E/EuPTF1/ClVesS6dcwa7LSCRbYh2KRJnHmU4H26MGzVEzSLeuWcBVi+qHpV+/c9miCU1hCwoTcVU5DZnl6/Fj++h88qdY3Uft/o55LSRaPo/l9rH35ABf+cXW9CCbzsEoJwYiDEQT6MnCriKXSjhucLA3xGAsQTSh4w7bXinVRW7efn8H9z/8Sw50D0DtBez4BHapAdbMqea3u4+mW+8din3aKPU4qS/1IUl2jEWy7MdSnidDOV3QWHShCnJFCMcopE4OErB/z076H/0hYGEWV2Ks+QqV8xbTH03Y7ehxnWA0wcadh3ll73F2H+8jnDCQJVAlGQmZ3nCcuGGkJ5dL2HM5ukIx1Ogg9z34Eu0ngxTN0ii+4CJCcbvX5MpF9Vy1qD6dXq4pdhNLGLZoAA2lPmaUeMbs7D5S0FgYIglypWCFI7MmARgxNZv6miKXymBMz3o+Vb5+YiDCCXc1asMC9LKZxJd8FlQnJwdjaZ/U1DWhcyBKT6Qv6fhu//VOmCbo4FRlLCs543OIDyueYrqKZ+Jy1eKb03zK0FmS2LLvBL++4TPpk0Kpx5FOnZ6Lr0smogtVkCsFJxxZRVGDUfpjCSQLSjxOKodkN179+AQ7j/cRSeh4VIXmGaWsnl3NpTPc/Pjuv8WlXc7xoIpugb7uf2AkR+TY3qoGTtX+3KFIKLIdoNRNK32tsJveJHTLotrtwDBMyjwuBuIJLN1CkizKvW4G4wk61BmgwrET/aeuIWRnSFInhYl6k4suVMFYyYtwaJp2D7A6+fPvAt5lnNzqM+MSJwdjdqpSkogZJm5VyWo1P9ofTl8donGdN/ef4I3fPsFdb22EeBR/+xGirV9HliWQFKSMKeEWEIrrKJLETL8Hw0wNIrb/6qumhUXylIHFDL+XqGEyq9xOmXbub0c+fpDI7E8T1mVUVcY0rfT1BexryGgBSvEmF+STSc+qaJp2KdAcCARWAuuBH3EObvWpIqtUyjQzo5FKXUrYAcTM7EaWUxqQOHmUxJN/j7XlVxCPUjL/Yso+9/X0tcGCYRM5bWsBu9MtFbgs8zjT2Y7UjFH7OZmWxkrAHiwc27sdfbCfvsMHKPfYad6Uj29qvZkO7wLBVCIfJ44twDvJj/sAH2fpVv/QW+08//HJ9JF96cwyukIx3KqSTl2mGkMTyRMBQCRupNvNJSMB25/D8d4LSJaJ5fXD6g3Ur7wUhyLhjnQn1VUirOtI2AVgTlVmRrGHYCxBbzSO5vSzqqmKvmginZ3oi8SJGyYzij1c09zALW0af/MfL/DM1ncwTJPKpgVE/Y1Z8zN6o/Gk+5nFpXNHzpAIBPkmH4ZMBhBKfvoN4FngioyrSScwYyyvtfG9ffTG7AKpjkiYw53d9MdNKtwqpmVbD+rJ2TqKJBGN2D/WIVno8QiSZWIMdCN/8DJYFon5q5BXXI3i8hKNhIgDxaqEaZoM6gamCbJkocoSFW6FcodFqUMlqhvcPM9DjdeZdpr3SQY1fgcLKzx8bUEFHkeUZ55+mtC2zbRVOZi1agWXLPs0P/h9B4ODgwCUqlDiU9BNi2KnwhXlCd5/772CcHHfvn17vpcwqRT6fvMWHNU07Wps4fgssDfjqTFPoS0uKkJ3Zk/dig9G8HhdqLJMlRFKxzgqfS78xT5My2K510FIclJpRuiSa2H1dYR9lSh1c3GoMqUeJ8VFdnCyjCiWBbFgmJhhV4LWlnhoSAYvAWa6VD67qgWXqrD8kpG7TNvb29m7dy9V1TVoi5dSV1VOa8tyronvGrGG4qpF9Sy/eEFBWCAWgnt7LhTCfqecWz2ApmlXAN8D1gcCgX5N0wbHy62+1O3g0rm1vHe0h+piF06HjGSB3+PE51SoOPoBW3/5z7R95SZKGpex63gf4YvakHSDmG6SMEx6w3EGY/YMC7/HyayyIqqL3RzsCdEbiaXrMGDkQqmhgcuYbvBh+35e33ecvtIGnt1nogaOck1kV7ridKT0qrBAFExVJl04NE3zA/cC6wKBQKqN8yXGya2+wufmu+suAsiq43h/Tzv/9wffY+NrrwFgHdzJ47f/ZbqO4+9f3cWj2w8QjCVIGHY5eDRhUuo9VVPRVO5D7ZMYiCWI6kY6vTtaHCIzNfzhsRADztmUFc+kQVUYjJpZIjCSI5qwQBRMVfJx4rgOqAR+rWla6rEbgAdzdasf6jw29K9/nd+Lruv85Cc/4e677yYSiVBaWsqdd97JV7/6VSRJos7vtYcQH+ymMdldmur52H0iSH8kjpkcyydJEg1lPqK6zj9+YfkZ7RJ/8B8vsOV4FMXlIRTXsUqq6A7HkCSJUnW4CGSeUoQFomAqk4/g6M+An43wVM5u9esurOX5j0+OWiZ95MgRrr/+enbs2AHAtddeyw9/+EOqqqqAUyeC3310jLcOduFKxjfqS31Ylu3xmsrGZA77rfS5zygaO/d8xG83bcR0eCj61FoShmXbLSY7WUt89veOJgLCAlEwlZnWlaPfWDGPb6xaOGoFZXV1NfF4nMbGRu677z4uv/zyrOdTMQSwS8Izi69m+r0UOx0EY/Fhw37PVFvR3t7Or554knAsgb/uApwuJw4lgpG0cEwYVtrO8XQFXqL5TDBVmdbCAcMDkc889xxN8y9ibsMMXE4njz76KDU1Nfh82X6oQ2MIZW5nOgPTEYzQG4kTTxh4XSpdg1H8HmdWVmM0UvM03IpM7bxFqI0L7auJx5k2nnYotpnTmURANJ8JpirTXjhSHD12jA03fYs9b76Kf8lqFv/XPztt6nJoDCFVhNURjNh9KIpCTbGH+lIvhmWxZk4NN7bMpc7vHTUVmjmEp3XlCjxU8fRuuw2/vtQWrt5wjBKXis9xZiNm0XwmmKpMe+EwTZOf//znfPevbycWHkR2uiiqa2Igmjht6nJoDEGSJGb4PXSFozgVleYZflRZxgI6+sM8+PZeXt7bQVWRe0RBOnnyZFo0WlpaWLt2LWuSnbCpE8OCGj9ts6v58tLZHNm7m5XLx5ZSFX0pgqnGtBaO/fv38+1vf5u33noLgBJtKQ1X3oizzA5+SjBq6jIzhiBhz/LsDscYiOq4HQod/RHqS70c6Q/TFYphWnYWZLRaisrKSlpaWjBNk7Vr1yJJEookjXpi6JymFaACAUxz4fjyl7/M4cOHqaiswr32OqqWrMqedcGprEWFzzXszZu6JqQ8RxyKjNuh4FBkukJRTCyCyWE9DkVKd75mplEdsoQsy0iSlDZdGroGcWIQFBrTWjiuuuoqgsEgt33/dm7a+MGIqcsyj5NHt+/n9QOdI5ZtD/UcOZo8YUiSRG84gWGayBKUuV1Z2Y2ecIx3P9zFR394hw0bNlBSUjJMMASCQmVaC8dtt92Gx+MBRp+bKUsSz+45OmrZ9rFgmM6BKD6X/auoKnJjWdAXiRHVDdyqTJnHldXBCuAe7GLrCx8iYbF7925WrFgxSbsWCPLPtBYOOSM4OVLqsq2piq0HTo5Ytv3qxyfQDZPN+zvZ1z1A3LCb5RQJDMsCS0JVZKqK3OnnUoQ7j1DbuRup0Y5rtLS0TPBOBYKpxbQWjkxGSl12h2Js3HVkxBTmruN9dIWieBwqsgzRmJGeE0pyDI/HqVBb4uVw7yCdoShlHifuwS5qO3ezvKEinT0RVxTB+UbBhfZTgUiXqqRTrkPRTYvBmI5Dke2pYBY4ZRmwMJIpVIdip2Ity6KxrIimsiL+pqWWy6RjtDRWsmLFCiEagvOWghOOTIY6mFnA4b4QOzt66Y/G2XOin4O9IXTTwu1Q8DoUJMDjUHCrMnrG1LD+aJxgTxcSljhpCM57CuaqMhqZsY+dHX0EYwnKvE4kyfY1sWd7WjiTLu6KfMrN3SFL6T6Vcq+L9ZevYfG8C5g9e7YQDcF5TUGfOOBU7OMX17cxt7KY5tpSZpUVUe5xJYcN26Qa9EtcKlj2NPNSj5N493ESkRBrL6jB7VCZM2eOEA3BeU/BnzhSDMZ0QnF9WG9KbzSOYkpUF7lQFRm/S6U/piNZdso1tHcbCxpquWn5FflcvkAwpThvhGOk3pSGMh8zLS9ORebxr38Gl6qkMzJ79+7lV0/sxL24kdaVK/Am60UEAsF5cFVJMTRQmsn6+XWUuJ3pjMzB/ft49ulN+BwKrStF9kQgGMp5c+KAsc23yGyNF9kTgWBkzivhONN8i+7ubiEaAsEYOK+EI8Vo3aoVFRW0traSSCSEaAgEpyFfvirNwEbg/kAg8E+apjUwTqbTZ4NhGCiKffJoa2uz07RCNASCUcmH6bQP+Efg5YyHz9p0+lxpb2/n4YcfJhgMph8ToiEQnJ58ZFViwB+T7da2FtiU/PhpYN1kLCQVCO3u7mb37t2T8SMFgoIgH74qOqBnmDEB+M7GdPp03pZn4tChQ2zevBnLsli0aBGqqk66UXChGxNncj7tFQp/v1MxODrme0JzczMuV+7GRCkD6Nra2rxlTwrBmHisnE97hcLY75lMp6dKAdigpmmp0sxzMp0+E6JOQyA4d6aKcKRMp+EcTafPRFdXlxANgeAcyYdb/TLgPqAJSGiadi1wPfDvuZpOnw2tra3U1dUxa9YsIRoCwVmSj+DoduwsylByNp0eK/v27aOyshK/3w9AU1PTRP0ogeC8YKpcVSaM9vZ2nnzySR577DEikUi+lyMQFAQFLRyZgVBN03C73flekkBQEBSscIjsiUAwcRSkcAjREAgmloITDtEaLxBMPFOxcvScqKioYNWqVcTjcSEaAsEEUTDCkdkav2rVKtEaLxBMIAVxVWlvb+ehhx6iv78//ZgQDYFg4pj2wpEKhPb09LBnz558L0cgOC+Y1leVAwcOsGnTpnQgVLjGCwSTw7Q+cbzwwgsieyIQ5IFpLRxCNASC/DBdryoKwNKlS2lpaSEej+d7PWdFLDZp85jzzvm0V5j++814TykjPS9ZIzibTXW2b9/eBmzN9zoEgvOA1cuWLXt96IPT9cTxLrAa20rByPNaBIJCRMGe/fvuSE9OyxOHQCDIL9M6OCoQCPKDEA6BQJAzQjgEAkHOCOEQCAQ5I4RDIBDkzHRNx047NE27BzuFrAJ3Yae5foGd9uoAvpZhgzntSRps7QTuxDYYL8i9app2PfAdQAduBz6kQPeaiThxTAKapl0KNAcCgZXAeuBHwP8BHggEAquBj4Eb87jEieCvgZ7kxwW5V03TKoAfAG3AlcDVFOhehyKEY3LYAnwp+XEf4MP2ltmUfOxpYN3kL2ti0DRtPrAQeCb50FoKc6/rgJcCgcBAIBDoCAQCN1G4e81CXFUmgUAgYACh5KffAJ4Frsg4wnZiV+kVCvcB3wRuSH7uK9C9NgFeTdM2AWXAHRTuXrMQJ45JRNO0q7GF45tDniqY1l5N0/4U+H0gEDgwypcUzF6x91IBfAH4OvBvZO+vkPaahRCOSULTtCuA7wGfCwQC/cBgMoAIgyRaSwAAAaxJREFUMBM4lrfFjS9/AlytadpbwH8Hvk/h7vUE8GYgENADgcA+YAAYKNC9ZiGuKpOApml+4F5gXSAQSAUMXwK+CPwy+f/v8rS8cSUQCFyX+ljTtDuAT4BWCnCvwAvYZul3Y19VioDnKcy9ZiGa3CYBTdNuwr7/tmc8fAPwIOAGDgL/LRAIJCZ/dRNHhnA8D/ycAtyrpmk3Y18/Af4WO81ekHvNRAiHQCDIGRHjEAgEOSOEQyAQ5IwQDoFAkDNCOAQCQc4I4RAIBDkjhEMgEOSMEA6BQJAzQjgEE4amadWapvVrmiZnPPacpmnX5nNdgnNHCIdgwggEAp3AcaAZQNO0DYAVCASeyOvCBOeM6FURTDRbgVZN0z4B/g74o7yuRjAuCOEQTDRbgcuARcDDp2m3F0wjhHAIJpqtwD9gt5d/Os9rEYwTIsYhmGgOAk7gm4XYJXq+IoRDMNH8GfCrQCCwOd8LEYwf4qoimBCSA4t/g33iEOnXAkPM4xAIBDkjrioCgSBnhHAIBIKcEcIhEAhyRgiHQCDIGSEcAoEgZ4RwCASCnBHCIRAIcub/AxFwMhHwHF0sAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from sklearn.model_selection import train_test_split\r\n",
    "from sklearn.linear_model import Lasso\r\n",
    "from yellowbrick.datasets import load_concrete\r\n",
    "from yellowbrick.regressor import prediction_error\r\n",
    "\r\n",
    "# Load a regression dataset\r\n",
    "X, y = load_concrete()\r\n",
    "\r\n",
    "# Create the train and test data\r\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)\r\n",
    "\r\n",
    "# Instantiate the linear model and visualizer\r\n",
    "model = Lasso()\r\n",
    "visualizer = prediction_error(model, X_train, y_train, X_test, y_test);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "# 3 alpha选择\n",
    "正则化设计用来惩罚模型的复杂性，因此alpha越高，模型的复杂性就越低，从而减少了因方差（过拟合）引起的误差。另一方面，过高的Alpha会由于偏差（欠拟合）而增加误差。因此，重要的是选择一个最佳的alpha，以使两个方向的误差最小。\n",
    "\n",
    "AlphaSelection可视化工具演示了在线性模型正则化过程中，alpha的不同值是如何影响模型选择的。一般来说，正则化对α的影响更大。\n",
    "\n",
    "\n",
    "|可视化器|AlphaSelection|\n",
    "|-|-|\n",
    "|快速使用方法|alphas()|\n",
    "|模型|回归|\n",
    "|工作流程|模型选择，超参数调整|\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "## 3.1 基本使用"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/envs/python35-paddle120-env/lib/python3.7/site-packages/sklearn/model_selection/_split.py:1943: FutureWarning: You should specify a value for 'cv' instead of relying on the default value. The default value will change from 3 to 5 in version 0.22.\n",
      "  warnings.warn(CV_WARNING, FutureWarning)\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import numpy as np\r\n",
    "\r\n",
    "from sklearn.linear_model import LassoCV\r\n",
    "from yellowbrick.regressor import AlphaSelection\r\n",
    "from yellowbrick.datasets import load_concrete\r\n",
    "\r\n",
    "# Load the regression dataset\r\n",
    "# 加载数据集\r\n",
    "X, y = load_concrete()\r\n",
    "\r\n",
    "# Create a list of alphas to cross-validate against\r\n",
    "# 创建不同的alphas值\r\n",
    "alphas = np.logspace(-10, 1, 400)\r\n",
    "\r\n",
    "# Instantiate the linear model and visualizer\r\n",
    "model = LassoCV(alphas=alphas)\r\n",
    "visualizer = AlphaSelection(model)\r\n",
    "visualizer.fit(X, y)\r\n",
    "visualizer.show();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "## 3.2 快速方法\n",
    "上面的相同功能可以通过关联的快速方法alpha来实现。此方法将AlphaSelection使用关联的参数构建Visualizer对象，将其拟合，然后（可选）立即显示它。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/envs/python35-paddle120-env/lib/python3.7/site-packages/sklearn/model_selection/_split.py:1943: FutureWarning: You should specify a value for 'cv' instead of relying on the default value. The default value will change from 3 to 5 in version 0.22.\n",
      "  warnings.warn(CV_WARNING, FutureWarning)\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from sklearn.linear_model import LassoCV\r\n",
    "from yellowbrick.regressor.alphas import alphas\r\n",
    "\r\n",
    "from yellowbrick.datasets import load_energy\r\n",
    "\r\n",
    "# Load dataset\r\n",
    "X, y = load_energy()\r\n",
    "\r\n",
    "# Use the quick method and immediately show the figure\r\n",
    "alphas(LassoCV(random_state=0), X, y);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "# 4 库克距离Cook’s Distance\n",
    "库克距离是对观察值或实例对线性回归的影响的度量。影响较大的实例可能是异常值，而具有大量高度影响点的数据集可能不是适合线性模型的良好预测指标。该CooksDistance可视化显示了索引的所有实例的干情节及其关联的距离分值，用启发式的阈值一起迅速显示该数据集的百分之多少可以影响OLS回归模型。库克距离具体介绍见：\n",
    "[http://sofasofa.io/forum_main_post.php?postid=1000622](http://sofasofa.io/forum_main_post.php?postid=1000622)\n",
    "\n",
    "\n",
    "|可视化器|CooksDistance|\n",
    "|-|-|\n",
    "|快速使用方法|cooks_distance()|\n",
    "|模型|通用线性模型|\n",
    "|工作流程|数据集/灵敏度分析|\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "## 4.1 基本使用"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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dddex/fbbc9lll9G3b9+WNJ9++mnSGsNHH33EHnvsQWlpaaD0Z555ZtwO+6uuuoqDDz64zfRTTjml1ef999+fZ599lhNOOCHhNtJhz/obYzqd6dOnc/LJJyecP2XKFBYtWsSVV17JyJEj6du3Lw8//DCffPIJ1157Lc888wzDhw/n2muvpby8nLPPPputt96ad999t+Xqf8qUKfzsZz9rs+7DDz+c3XbbjSuuuIL58+czbNgwwKnRbLHFFnTv3h2A6upqevTo0WrZ1atX07t378Dpn3zyyQxLyNG7d2+++OKLdq3DzwKGMSYjQWoEBz92aco0u10whN0uGJLWtt99912uv/76NtMXLlzItttuS58+fdhrr71oamrio48+arnNdM8992T16tU0NTWxww478PDDDwNw6aWXcsstt3DHHXdwwgkn0NzczIsvvthm/UuWLOEPf/gDK1as4IILLmDw4MEt82L7I2699VZ++9vftlmHNyxHkPRBaxiJainx9qE9LGC4bNgEYzqHL7/8kvLy8ri3+L7//vusWLGC6667jq+++ora2lr69evHggULOPbYY1mxYgXl5eUtTUIAr776Kvvvvz/bbLMN2267LStXriQajbL99tu3Wve0adOYM2cO5513Hvvtt1+bbfv7I+bOncuSJUt46KGHOP/881vSbL/99i1X/EHSB61hzJ07lyuuuIIhQ4bw4YcfMnnyZMC5e8qr0WSDDT7osv4KYzqHNWvWtLpTac2aNS39DiNGjGDt2rWceeaZXHjhhdxwww2ceuqprFixgpEjRzJu3DhuvPHGlmUbGxuZPn06Z511FuD0AUyePJk777yzTZPXsGHDuPfee+MGC3ACgHelX1FRwY9+9KNWJ3+A733ve6gqTU1NgdIH9cknn3DSSScxevToVsFw/vz5HHjggRmtMx6rYRhjOpWBAwfy0EMPtXzu1asXN910EwCbb745EydObJW+pqaGO++8M+66unbtyv3339/yuX///kyZMiVu2lQPLfq3q6rsueeebdJ069aNo48+mpdffjlQ+qA++eQTjjrKGTHJa/Kqq6vj9ddfZ8qUKUSj0YzX7Wc1DGOMybKKigqmTZsWd/iNn//850ydOpXq6upA6YOoqqpi5513Zu3atS13jk2ePJkxY8Zk9aVXVsMwxpgsGzJkCEOGxO/I32qrrXj00UcDpw9iwoQJAPTs2ZOrrroKoOX/bLIahjHGmEAsYBhjjAnEAoYxxhSZTDvBLWAYY1Lq0qULjY2Nuc6GyZKmpqa4AyymYp3expiUunbtysaNG6mtraW0tLTl1s3OoKGhoeV9HsXKK4NoNEpTUxNNTU107Zr+6d9qGMaYQLbeemvKyso6VbAAMr5VtZB4ZVBSUkJZWRlbb711RuuxGoYxJrBMrkrzQWd8U2C2ZaMMrIZhjDEmEAsYxhhjArGAYYwxJhALGMYYYwKxgGGMMSYQCxjGGGMCsYBhjDEmEAsYxhhjArGAYYwxJpBQH9sUkUnAQUAUGKuq833zjgImAE3ALFW92Z1+G3CYm7dbVfUZEXkEqAS+dhe/XVVfDDPvxhhjWgstYIjIEcDuqjpIRPYC/ggM8iW5CzgWWAG8KSJPAzsAA91ltgU+AJ5x01+jqi+ElV9jjDHJhdkkNQR4DkBVFwEVItIdQER2Adaq6jJVbQZmuennAsPd5b8BykWkNMQ8GmOMCSjMgNEbWOP7vMadFm/eaqCPqjapao077Tycpqom9/MYEXldRKaIyHYh5tsYY0wcHTn0ZLIxkVvNE5FhOAHjGHfS48DXqvqhiFwN3AiMSbaxXW95lueH7R44c954+ZFIJOm0zqSz5jubrAw2lUFnP57boxj3OVY2yiDMgLGSTTUKgL7AqgTzdnSnISLHAtcBx6lqNYCqvuZLOwO4L9XGd+yxBZWVlYEzWza7CqDVMvGmdRaRSKRT5jubrAxal0FnPp7bw46DYGVQV1fHwoULk6YJs0nqFeA0ABHZD1ipqhsAVHUp0F1EBohIV2Ao8IqI9ABuB4aq6lpvRSLytNvvATAYSL5Xxhhjsi60GoaqzhORiIjMA5qBS0VkNFCtqs8CFwNPucmnqupiEbkQ2A74i4h4qzobuAeYKiK1wLfAT8PKdxDjZ0aYOOdjmiaOymU2jDGmQ4Xah6GqV8dMWuCbN5fWt9miqg8CD8ZZ1efA/lnPYIamL6iif0V5rrNhjDEdyp70NsYYE4gFDGOMMYFYwDDGGBOIBQxjjDGBWMAwxhgTiAUMY4wxgVjAMMYYE0hHjiWV19bV1rO+riHX2TDGmLxlNQxXTUMjpV2SjY9ojDHFzQKGMcaYQCxgGGOMCcQChjHGmEAsYBhjjAnEAoYxxphALGAYY4wJxAKGMcaYQCxgGFOExs+MUDru8Vxnw3QyFjCMKUL21kiTiYINGNUbG+wKyhhjsqhgA0ZtY5NdQRljTBYVbMAwxhiTXRYwjDHGBGIBwxhjTCAWMIwxxgQS6guURGQScBAQBcaq6nzfvKOACUATMEtVb3an3wYc5ubtVlV9RkT6AY8DpcAqYJSq1oWZd2OMMa2FVsMQkSOA3VV1EHAecFdMkruAU4FDgGNEZG8RORIY6C5zHDDZTXsTcK+qHgb8Gzg3rHwbY4yJL8wmqSHAcwCqugioEJHuACKyC7BWVZepajMwy00/FxjuLv8NUC4ipcBgYIY7fSZwVIj5NsYYE0eYTVK9gYjv8xp32nr3/zW+eauBXVW1Cahxp52H01TVJCLlviao1UCflFuPRqmvrycSiaRM6qUHWqWvr69vMy3Z9HyT7/nrCFYGm8rAf9zW19ezvr6J0nGP896Ze+cyex3CjoPslEGofRgxkr0wu9U8ERmGEzCOSXM9vlQllG22GZWVlcFyN2URQKv0ZbOr2kxLNj2fRCKRvM5fR7AyaF0G/uO2bHYV/91YS/+K8oIvIzsOgpVBXV0dCxcuTJomzCaplTg1CU9fnA7rePN2dKchIscC1wHHq2q1O/9bEdkiNq0xJn3jZ0aoWleTOqExMcIMGK8ApwGIyH7ASlXdAKCqS4HuIjJARLoCQ4FXRKQHcDswVFXX+tb1Kk4HOe7/L4WYb2MK2vQFVZR2CVZRN8YvtIChqvOAiIjMw7kj6lIRGS0iJ7tJLgaeAt4CpqrqYuAMYDvgLyIyx/33HeBXwDki8hbQE3g0rHwbYzo/G749HKH2Yajq1TGTFvjmzQUGxaR/EHgwweqOzm7ujDGFyoZvD0fSgCEiWwLn4zwTMcCdvBSnSehhVbWGUGPy3PiZESbO+dhOoKbdEjZJicjRODWCAcA9OM9HDHf/HgB8ICJDws+iMaY97GrbZEuyGsaFwIExnc8A/wJmicgtwP3Aa2FlzhhjTP5IGDBUdXiiee78r9n0VLYxxpgClzBgiMgynEEDY5UAUVX9Tmi5MsYYk3eSNUkd2mG5MMaYDuLdBNA0cVSus9LpJAsYp6rq/yVbWEQuT5XGGGPyid0EkLlkAWMrEZkLTAJe8W6hFZFynGciLgf+Gn4WjTHG5INknd43ichLwLXAoyJS784qw7kzapz/hUjGGGMKW9IH91T1PeDHItIF2Nad/LX7DgtjjDFFJNDQIG6AWJMyoTHGmIIV5mi1xhhjCogFDGOMMYGkbJISkQqcFxr1VtWRInIS8I6qWhOVMcYUkSA1jIeAz4Gd3c/dsPdRGGNM0QkSMHqp6l1APYCqTge2DDVXxhhj8k6gPgwR2Qx3XCkR2QGwxySNMabIBLmt9m5gPtBHRGYABwBjQ82VMcaYvJOyhqGq04ChwBic/ox9VXVq2BkzxphE7J3duZEyYIjI3sClqjpNVWcAE0RkYPhZM8aY+GwAwdwI0odxLzDL9/lhnNe0GmOMKSJBAkZXVX3L+6Cqf8N5iZIxxpgiEqTTu1pELgbm4ASY44ANYWbKGGNM/glSw/gpUAn8BXgK2N2dZowxpoikrGG4Q4Ccn8nKRWQScBDOMxxj/e/PEJGjgAlAEzBLVW92pw8Engcmqeo97rRHcILW1+7it6vqi5nkyRhjTGaCjCX1E2A80BNf34WqfifFckcAu6vqIBHZC/gjMMiX5C7gWGAF8KaIPA1U4Tz38VqcVV6jqi+kyq8xxphwBGmS+jXOg3qHA4f5/qUyBHgOQFUXARUi0h1ARHYB1qrqMvddG7Pc9HXACcDKNPfDGGNMyIJ0en+qqnMzWHdvIOL7vMadtt793z/a7WpgV1VtBBpFJN76xojI5W7aMar6VdKtR6PU19cTiUSSJvOnB1qlr6+vbzMt2fR8k+/56whWBpuO11bc4z2t30geSfUbjJ0f5Hdd6LKxv0ECxjwRmYBzl1SjN1FVX09zW8luxU11m+7jOK+G/VBErgZuxHnyPMkaSyjbbDMqKyuD5W7KIoBW6ctmV7WZlmx6PolEInmdv45gZeCUQVlZWdsZG52fcllZWacso1S/Qf/82OOgM/x+sy3Ib6Guro6FCxcmTRMkYBzl/u/vf4gCqQLGSpyahKcvsCrBvB1J0gylqv4+jRnAfSm2Hap1tfWsr2vIZRaMMabDBblL6kgAESlR1Wga634Fp//jARHZD1ipqhvcdS4Vke4iMgBYjjNW1VmJVuR2iF+pqkuAwUDyMBiymoZGSrvYs4vGmOIS5C6p7+MMB7IVsKeI/C/wiqq+m2w5VZ0nIhERmQc0A5eKyGigWlWfBS7Gea4DYKqqLhaRSmAiMABoEJHTgFNwhiKZKiK1wLfYcyDGNX5mhIlzPqZp4qhcZ8WYghekSeoe4FzgTvfzVOBPwCGpFlTVq2MmLfDNm0vrZi5UNYJTg4j1BrB/gLyaImOD0BnTcYLcVtugqh95H1R1Mb7Ob2OMMcUhSMBoFJGd2fTGveMpwsEHbfx9Y0yxC9IkdQXOUB0iItXAUuCcMDOVj6zpwxhT7ILcJfUR8D0R6QXUqer68LNljDEm3wS5S+px3OYo9zMAqnp2eNkyxhiTb4I0Sb3q+7sMOBL4TzjZMcYYk6+CNEk9GjPpDyJio8a67DkAY0yxCNIkFXsnVT+clygZOmdnuAU5Y0wmgjRJNeL0YXi30lYDvwstRyZ0nTHIGWNyL0iTVJBnNYwxxhS4hAFDRG7Gd3dULFW9IZQcGWNMB7Nm2mCS1R4acd63nehfUWtujtqT38YUCGumDSZZk1QvVR0jIveoavKXFRWhKNgBZowpKskCxjEi8hQw2HsXt589uGeMMcUlWcA4HjgY+AHwWpJ0xhhjikDCgKGqnwGficg8929jjDFFLMhzGAe4r0itwDesuap+J7RcGWOMyTtBAsavgfOBqpDzYowxJo8FCRifuq9TNcYYU8SCBIx5IjIBmIPv1ayq+npYmTKmENjDYKbQBAkYR7n/D/JNiwIWMIxJwh4GM4UmyFhSR3ZERowxxs9qaPkn2VhSd6rqWBF5izhjSqnq4aHmzBhT1KyGln+S1TD+6P5/faYrF5FJwEE4AWesqs73zTsKmIAzLtUsVb3ZnT4QeB6YpKr3uNP6AY8DpcAqYJSq1mWaL2OMMelL9uDeAvf/NzNZsYgcAeyuqoNEZC+cAOTvB7kLOBZYAbzpPutRBdxN2yfLbwLuVdVpbgf8ucB9ybYfbY5Sta4mk6wbY4yJI8x3XQwBngNQ1UVAhTcmlYjsAqxV1WWq2gzMctPXAScAK2PWNRiY4f49k00d8QlFgdIuJamSGWOMCSjMgNEbWOP7vMadFm/eaqCPqjaq6sY46yr3NUGtBvpkO7PGGGOSC3JbbbYku9xPpyoQPG00SiQSCZwWaJW+vr6+ZZr/by+tNy12uXyRKE+t9qWTS7UvudzHfCln/3HawncM5zp/iSQrv1RlGzs/0e866PoKQTb2LcyAsZJNNQqAvjgd1vHm7UjbZii/b0VkC7f2kSrtJiUlVFZWBsvtlEUArdKXza5qmeb/mymLIBqlrKysJW3g7XSQSCSSME+t9qWTS7YvycqgI+RDOUcikVbHaYuNzjO4ZWVleXscJCu/VGXrnx97HMRbNh++qzAF+S3U1dWxcOHCpGnCbJJ6BTgNQET2A1aq6gYAVV0KdBeRASLSFRjqpk/kVeBU9+9TgZfCyrQxxpjcKoogAAAavklEQVT4QqthqOo8EYmIyDygGbhUREYD1ar6LHAx8JSbfKqqLhaRSmAiMABoEJHTgFOAXwGPichFOHdSPRpWvo3JJ/bwmsknofZhqOrVMZMW+ObNpfVttqhqBOeOqHiOzmrmjOkE7OE1k0/CbJIyxhhTQCxgGBOidbX1lI57PNfZMCYrLGAYE6KahsYOaVIaPzNigcmEzgKG6fTsKt76OkzHsIBhOr2Ouoo3pthZwDDGGBOIBQxjjDGBWMAwxhgTiAWMNFjnqjGmmFnASIN1rhpjipkFDGOMMYFYwGiHdbX19hpYY0zRKIqAEdZTsDUNjfYa2DxnT0Abkz1FETDsKdjiZd+9MdlTFAHDGJMbVsMrLEUdMMI8mO2HYozV8ApNUQeM6Quq6N5ts1BO7PZDMcYUmqIOGGDPVhhjTFChvqI1X6yrrWd9XUOus2GMMZ1aQQeM5uYopeMep7RLid3+aowx7VTQTVJR6LDmJuvkNsYUuoIOGB2ps3Vy20CKxph0WcAoUtbZb4rB+JkRDnjy41xno2BYwEjTutp6mpqjLZ+bm6OhjCdlTVzGtN/0BVX0Kd8scHr73SUXaqe3iEwCDsLpThirqvN9844CJgBNwCxVvTnRMiLyCFAJfO0ufruqvphpvsbPjDBxzscZXWHXNDS2+hyFUDrUO1sTl0nOO+aaJo7KdVZMEva7Sy60gCEiRwC7q+ogEdkL+CMwyJfkLuBYYAXwpog8DfRKssw1qvpCNvJmB4XpaHbMmUIQZpPUEOA5AFVdBFSISHcAEdkFWKuqy1S1GZjlpk+4TD6LbZYaPzNiw54bILwmS2NyIcwmqd5AxPd5jTttvfv/Gt+81cCuwHYJlgEYIyKXu2nHqOpXQTLx1bcbaWqOUloCkYiz6vr6+k0JolHnc9Tpl/DS+NNFIhHq6+tpbo6yqfeClmWiQGmJkz4SifDk/E9bfQa464MveWLR17x35t5Bst1q25lKtKy3v/78dVap9iUb5ZhIqu+0vr6+1bEBcM5Ds0I5DpKla3W8e9xjN+xjoD3lH2Sfkh7jPol+10HSF4ps7FNHPriXrKE/0Txv+uPA16r6oYhcDdwIjAmy0f82uaf4khIqKysBKJtdtSnBxkbKyspgo9M34aXxp6usrKRsdhXRmpinxUtKWn54lJRQVlbWktZbr7e+t2Y/Q/+K8lbrT8a/7UxEIpGEy8bLX2eVbF8ikYjz3ZJ5OSaT6jstm10FNQ0txwbAW1/8N+PjIFk/SKLjxV8GrbjHe9jHQHuO42TLplqv/zdeX1+f8HcdL32m+c1nyc4Hnrq6OhYuXJg0TZhNUivZVDsA6AusSjBvR3da3GVU9TVV/dCdNgPYJ5sZjb3zKahMlmkvu4ujcKT7XRZrP4gd8/kjzIDxCnAagIjsB6xU1Q0AqroU6C4iA0SkKzDUTR93GRF52u33ABgMJA+DaYq986mjZPJDKNaTRiHK1nfZ0X1mHX0Ct2M+f4QWMFR1HhARkXk4d0RdKiKjReRkN8nFwFPAW8BUVV0cbxk37T3AVBF5EzgR+HVY+e5I9kMIR0ed0PLlne7TF1R16FhpdtyGJ99rU6H2Yajq1TGTFvjmzaX1bbaJlkFV3wD2z3oGTUHqqBNae9/pbqMom1j5HoztSW9jcqS9AQfsFu5cyPdaQDrS3ZeSaLTjO27DFIlEBgD/mX/mY9R9uaHlRqaSEjjulhHscckx7PKbZzjt6Xfp//lXLR3XXpr9jvsBhz71C8bPjBC5+yVOiSxhpx5bsry6lsamTWV15egjaCrtQp+133Lls/MpKXGe+PbSNjVHmfnj/fnrny4G4LbvXEJ5TR079diyZR3Lq2v54PsDeOj1/wXgH1c+wbKn322ZB7BTjy0p33l7jnrNSXPCyLs5cfaHlG/Wler/NjCg56arkaPn3siWO21L/bpveW6fcXSLc3fM938zgh8u+ZLl1bVc/cI/qIxzhdvn2O9zwH3nA/Dx7TP49L6/tknTtbwbJ/7zDgC+eudT3j7zrrjfx2HTLqNnpdP9NEMuIxqnv0jGHs+eY08A4J3zH+DL19t2UVXsuzOHP305AEseeZN/3jS9pZyamqMtZX/CR7cjk2fRZeU6fv7k23QtLWkpR8/+955H3+N/AMBfD7+R2uVfE6v/iIP5wYSfAPDhtU9RNWVemzQfNDQxYcTB1N8+kpWzP2T+pQ+3mu8dM7cNP4hu/bej9ptarnnodbqWOnn1TvT9K8rZ54bT2GX0EQDMPfX/WPfBf1rW4eV/bs+tePbH+7Pk+lP45M5Z6J2zW/YfnOOv33bd+ZFOAmBtZAmvDvsdaza2LfN7jvsBn/WtYKceW3L31Hk01tS1SbP7xUez95U/AuC9ix9i1csL2uSpx3f7MXjmeACWPvk2C66f0qYMAC74952UVWxF7fKv+evhN7bZFkDlpHPYadj/APDqkJvRD5e2mr9Tjy3pd+qB7Hf7SHb5zTP88PV/cdLS1W3W0237HlwydD8Adv3sS4Y9P59+22z6nXh5Gvn2TfTYc0ea6hu5v89FbbYF8N1rfsxuFwwB4G8/uYuv3/201f4D9Dp0Tw5+zGk9X/z7V1h0x8y4+zdsyd0AfPPPz3lz2O1x09z5w4EsHdCLJdefwqz9rqbhm7YXA7uedyQDrzsFgPfHPsKKmW1vl916j7788KVrAPh8+ru888s/xj0fXH/6IGq22px/XfBDXvvR7+jz+9MAdq6srFwaL39Ww0hg+oIqupRkfvUXjcKX3/43izlqraahseVk2NnNXLi8XVds0SitgjnAxoYmSvPs6K5paKQdh5QxOVewNYxhz3/KqpoGSruUtFyB1t8+EoBdfvNMS3rvaiFemuXVtezUY0uWXH8Ku/zmmaRVf+8K15823jaXXH9KyzLxpqWa5897omXdckh433XsvuVasnIIsmy8sl5eXcv2W3SlphHW1zWEMoZT2ZVPALRsN/Y5CX/evJon0FLuscsn2j+g5bjy/vbPj12vXyQSYXjMMwZA0mVSSef7au936xf0txO7bH19PctvGpF02aC/qyDbbo+w1p3ofODfnu85DKthdEb2zor2y0Y/QVD53mEZtkJq2zfxWcDIY/bOisI4CRXLeFLFHjD98uG4DSMPFjCKVGc5if3h75/mOgvtFsUZ4yYXIwOY3AgjeObDyAAWMIpUWO/xyLZUTUrrauMMrJeHLFSY9sqHGpwFDJNTQZ8jSHR1lathXeIJ+uR3On1T+fI0eS7ket/zoVkpW+764Mus7IsFDJ98bDLobB3fmVSbg9R0cnF1le6+BO1gT6dvqiM77WPl+oQZb99j8xRmHvPhij5bXvt8fVb2pWgCRj4GA0gcELwRdJMNHZGPwSSMH1mu+ls68wmjvSfS9rzGOEyx30ln/o46o6IJGGHL9KSW6GrT39QSe5XlVdW9YJJvQSPbvE7joOWb6XD1qeT6ijsd7T2RdvSAhqnk48URdK5jIhuKMmCE0TaazU7k8TMjSU94se32hXqF5S+HdMo3rH4Nu5rdpKNP4Pl6i3kYx0S+BkcowoAxfmaE9XUNoV09ZTIYXOwBMn1B2ydz/ZrztHktXanKKlU5dLRsXGjEXgg0N0fz9uSQTL6ewAtBPpdt0QWMdE5CmTQzTV9QlfRdtNC2GpvuAZLNcHHg5Fk5O2HlotkjnSaE2AARRgd0lGA1xHjBNXZaPl+ZejJpwsl2E2OywB/WnVnZbrrKVVNY0QWMdGTazJTq0J6+oIqy0i5UrauhqTlKUwd06iY6wD5YsTav2qo98U6Q2ThppNOEkMs7lGLFC66x0/L5ytSTSRNOtpsYve813m8irO88201XQdYXRvAruoDhPeiVrPaQ6TsG0jmh1Tc1t/qc6ADOlkQHWLMbsNqrPVeO/u1768l27cNbbzZ/QNkqu0LJRxCJTmK5uGL2fhOF+k4Rf/BbX9+UlX0suoDhXa0kqz3EnqyyeUAlW1cuOlWzdZrJ1pVjNstgfX1Ty4nU+06DBKGgJ69slZ2/KSmTE2fnCBWORFf3ubyhINHFyar1G1M2AyaS7av79p6Dahua20zLZJ1FFzAykc2r3UTrCtJfcuDkWaFdCXXU1V2iE2K89vd4nfuJlo/Xeez9SNLti/KPXxVWp7S/XX59XUPLyTLRiTOsW4XD5p04Y8uwowLEutp6VtW0fZYpyDHhbwVIt+ab7aat9p6D/EdOe2rxFjAI966jdK5WE3153onigxVrs5m1Vieg7t0265Cg4W8G8G9/Q5wHFON9K4keJovXeRz1/Z/OD8Or+TQ1R4myqWwSnbAzKbd02+XjlU9n4O1n7HfTUcN+1DQ0Eu89Y+keE5kGuKC//3Rqlu2tbbQnWBd8wEh2Vea1/YZ53ZbJl5OLAfXidZh6B3G22pf9B3rsKLTpfAepfiyJLgBi+0uCqmlobHXnW7LyCKNG0pzGMZrLO6WSBYFV6ze25KvZHcEg0Qk71fGWzphdTc1RmrLwA091Z1Wi30m833/QdMnSxjaZp/OdtydYF3zASCbIceRVXYPWQmJP9t6Xk86XFO/qM9kBkc6Xn+jqJN6J1DuIpy+oarnKjpcP/zoTNUF46/MO9ERX2Nm48oz3Tfn3L167tL8PIV5Z+KfEBjv/j9efLlHgT7eTOjaldyt0vHJKdKdUJuUa22zjL6d4TTpeM0y8W7Xrm5pbhnj39idRGfhPnv6y8n5HQZ+jClKLS9YJH7uuRNv0yjzoxaG/lp3od+0FoSDrTLW+dPYlla4ZLdVJHTh5VsofamyBe8NSBP15x4795H057W1S6F9R3vJazVixVxsT53wMQFNlZZsxgbyTdrJy8C/j/UC9LbQ0z0wc1Spd7NAd3vYOnDyL95d93WpaMu0pp6AnxHi3p3p5i/f+jdiLBa/GkagEUwXFeMt5Jwh/GcULXpkG1KAnCe877d5ts5Z8lo57nHGD9251HHlNOt73O27w3i15fX/Z13G3lcmFvn+Z0i4lrcrUOzaDPsfif32uxysXfwAs7VLS6jjwzgneMR5v37y8tFxYpSjrdbX1TJzzMWWlXVrW373bZi3B0P87CBokvTz7z2GZ7EsyRRUwvBNXurLRZBV2d6X3w+1fUU5plxK236JrxgPI3f3WJy1/ez8o72SwwTd+Vf+K8lYnkFjjZ0biBotkHbje1FQnRX9g9AQ9+JvcZqPYk4c3CkCiPEF6zUPp8MrVv9/xHjIN2vfhnWTS5QXP2IsTr6yr1tW0uvp/f9nXlPjme5qaoymHuAHanCz9+U+1bDoXF7H5ixX7Hfvz4h3/ifo9/OlrGhpbnfj934P/Fl7vjj2vY90Lhl7w8m/LH+xjv1dvff0ryluODS9tU3M07X1JJdSAISKTgINwvo+xqjrfN+8oYALQBMxS1ZsTLSMi/YDHgVJgFTBKVevCzHs2NDVH0/pSmpqjCX8oya4GmpqjcR/Ai23rTHWlEtuU5J28/KmjMekT8a6gYtPGXiVmqr1v4vN+vF5AXfZNTcqTCgQL/F5ASkfseoN2bPprP/7jxqsFHfDkpn3yrir7V5S3nJS8bfhrFqmuZr1l/DcVxBOkPEu7lLBTjy1ZXl3b5iHEVOKVmX+bsfsQ+zn2xJxovfGao/01wti5/psm/CfrqnXOMZYo6MSuJ94wMkHXl8m+1E44PeF6PCXRaDjXviJyBHClqg4Vkb2AP6rqIN/8j4FjgRXAm8BFQK94y4jIn3CCyjQRmQAsU9X74m03EokMAP4z7PlP495OV6j8VyYmmNir2kyl02RpUsvW95KPsv07zeb6+pRvxvPDdgfYubKycmm8NGHWMIYAzwGo6iIRqRCR7qq6XkR2Adaq6jIAEZnlpu8VbxlgMPAzd70zgSuAuAHDc/3Uv1P35YYQdssYYwpPtx22BidgJBRmwOgN+Lvn17jT1rv/r/HNWw3sCmyXYJlyXxPUaqBPppkqcWtv0Wjrv2Pnx05vz/r96wsyLd62S0o2NQ1FY+Z3KaFVP4M3qyTF34m2EW+ZdPm3EW//8G0/0fzYNP6/Y/fBW0eifWuVtxLo6mvnBWiOJl9vsv0owSn/xpjqfrw8xDvm4qWJ910nKyfipEt0vMXbVrzvPFuND0H3GTZ9L/HKMjavsbq630HsbztRGcR+36nKF9qmT3S8xKb3/vb3IcQKmgf/umNvYEnnK4vdl67xHliJ0ZGd3slyk2hevOmBivSnH91Gt27dgiQtSJFIhMrKylxnI6esDKwMwMoAgpVBXV0dCxcuTJomzOcwVuLUDjx9cTqs483b0Z2WaJlvRWSLmLTGGGM6UJgB4xXgNAAR2Q9YqaobAFR1KdBdRAaISFdgqJs+0TKvAqe66z0VeCnEfBtjjIkjtCYpVZ0nIhERmQc0A5eKyGigWlWfBS4GnnKTT1XVxcDi2GXc+b8CHhORi4Aq4NGw8m2MMSa+UPswVPXqmEkLfPPmAoNi5sdbBlVdBRyd9QwaY4wJrKjHkjLGGBOcBQxjjDGBWMAwxhgTSCEOPlgKUF/f8e+UyDd1dXk/3FborAysDMDKAFKXge+cWZooTWhjSeVKJBI5FHgr1/kwxphO6rDKysq/xZtRiDWM+cBhOA/8NeU4L8YY01mU4gy7ND9RgoKrYRhjjAmHdXobY4wJxAKGMcaYQCxgGGOMCcQChjHGmEAsYBhjjAmk4G6rFZFJwEE4L5Maq6oJbxErBCJyG85txF2BW3FuiXsc5xa5VcAoVa0TkbOAX+KMAvygqj6coyxnnfuulIXAzcBrFNn+A7j7Nx5oBG4APqJIykFEtgIeAyqAbsCvgS9wXuMcBT5S1YvdtFcCw93pv1bVWTnJdBaJyEDgeWCSqt4jIv0I+N2LyGbAI0B/nMcQfqqqSxJtq6BqGCJyBLC7qg4CzgPuynGWQiUiRwID3f09DpgM3ATcq6qHAf8GzhWRcpyTyFE470e/TER65ibXobgeWOv+XXT7LyLb4rwC4FCcd8sMo7jKYTSgqnokzvt07sT5LYxV1UOAHiJyvIjsDIxgUzn9n4gkfKq5M3C/07txLpQ86Xz3ZwLfqOqhwC04F50JFVTAAIYAzwGo6iKgQkS65zZLoZqLc7UE8A1QjnMwzHCnzcQ5QA4E5qtqtapuBN4GDunYrIZDRPYE9gZedCcNpoj233UU8KqqblDVVap6IcVVDl8B27p/V+BcPOzsa13w9v9IYLaq1qvqGpx36+zd0ZnNsjrgBFq/hXQwwb/7IcCzbtpXSXE8FFrA6A2s8X1eQ+tXvhYUVW1S1Rr343nALKBcVb1BY1bjPLkZWy7e9EIwEbjc97nY9h9gALCliMwQkbdEZAhFVA6qOgX4joj8G+ci6gpgnS9Jwe6/qja6AcAvne++ZbqqNgNRESlLtL1CCxixSnKdgY4gIsNwAsaYmFmJ9r8gykVEzgb+rqr/SZCkoPffpwTnCvsUnOaZP9F6Hwu6HERkJPC5qu4G/BB4IiZJQe9/Cunue9IyKbSAsZLWNYq+OJ0+BUtEjgWuA45X1WrgW7cTGGBHnDKJLRdvemd3IjBMRN4Bzgf+l+Laf8+XwDz3avMzYAOwoYjK4RDgZQBVXQBsAWznm1/o+x8rnd9Ay3S3A7xEVRMO9V1oAeMVnE4vRGQ/YKWqbshtlsIjIj2A24Ghqup1+r4KnOr+fSrwEvAusL+IbOPeUXIIBTCir6qeoar7q+pBwEM4d0kVzf77vAL8UES6uB3gW1Fc5fBvnDZ6RKQ/TsBcJCKHuvNPwdn/14ETRaRMRPrinDQ/zkF+w5bOd/8Km/pBTwLeSLbight8UER+CxyOc+vYpe4VR0ESkQuBG4HFvsnn4Jw8N8fp1PupqjaIyGnAlTi3E96tqn/u4OyGSkRuBJbiXGk+RvHt/0U4zZIAv8G5vbooysE9Af4R2AHn9vL/xbmt9gGci+J3VfVyN+3PgbNw9v96VX0t7ko7CRGpxOnHGwA0ACtw9u8RAnz37l1iDwG743Sgj1bVZYm2V3ABwxhjTDgKrUnKGGNMSCxgGGOMCcQChjHGmEAsYBhjjAnEAoYxxphALGCYoiAiPxCRuzNc9kwR6dDfioj0FpFpaS6zXEQGhJQlY+y2WmNSEZFPgb1UtTHXeUlGRJYDh6rq0lznxRSmgnsfhjHxiMhg4DeqeqiIzMF5GvZgYA/gV+5DTGfgDFxXgzOmzk9xHoTcDXhNRE4GzgDOBuqB/wJnqOo3IrIUZ1jt44GdgZ+p6msisjvwB5za/H9xHqJa4T5AdjrOb/AT4BL/IHJuTeFvqrqTiDyCM4TDPm5+H1bV20RkB+AvOO89iOAbB0hEJuA8zbsF8CbOuzIuwwl8F4iI4LxDYf9CHg3BZJc1SZlitZWqnoDzdPR4d9q1wBhVHexO21FVf+XOG+IOv7IFcIyqHoHzZPlI3zo3quoxOE9a/8Kddj9wu6oejvM08nAROQA4GTjcfZfJNzhjYSWzi6qeBByDM3YYwFjgHfddBo/ijJ2GiAx3836Eqh6AE/CG4rwjQkTkEOD3wEUWLEw6rIZhitUc9/8qwHuJ0CPAIyLyNPCMqr4bZ7mvgVki0owzHIN/cMt46zzQm+4Ow42IjMc5ib/hXOhTjjOsQ8r8qmqViHR3h3TYB3jQnf4PEal20x4JDHJrUgA9cN4P0Swi5+LUOKap6psptmlMKxYwTLHy90eUAKjqJBF5EufthQ+IyEOq+oCXSER2Au4Avquqq0XkjlTrxBm3J7YmXwfMUNXY4eiD5tdbfwnOmGke7+1xdTiv4IzNHziB7FvgO2ls2xjAmqSMAUBESt2BK6tV9VGcQR0PcmdHgc2A7YGv3GDRE6d5qFuKVc/DCUCIyBlu38LbwPHuoHmIyCUiMiiDbH8MDHLXcSDOKLUAfwNOEZGu7rwbRGR3Edkcp4nsJKBeREZlsE1TxCxgGIPz9kKcV33OE5HXcN7i512hvwS8D1QDn4rIe8C9OO/R/qlvGO14xgCXuM1D5wP3qer77vJzRORvOK/UzGRU5TuBI0XkdZy+lCXu9GdwgtI8Efk7ziiuS3De9fysqi7G6f/4tVtrMiYQu63WGGNMIFbDMMYYE4gFDGOMMYFYwDDGGBOIBQxjjDGBWMAwxhgTiAUMY4wxgVjAMMYYE8j/A8/TBvKD48BhAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from yellowbrick.regressor import CooksDistance\r\n",
    "from yellowbrick.datasets import load_concrete\r\n",
    "\r\n",
    "# Load the regression dataset\r\n",
    "X, y = load_concrete()\r\n",
    "\r\n",
    "# Instantiate and fit the visualizer\r\n",
    "visualizer = CooksDistance()\r\n",
    "visualizer.fit(X, y)\r\n",
    "visualizer.show();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "## 4.2 快速方法\r\n",
    "使用关联的快速方法，可以在一行中实现与上述类似的功能class_prediction_error。此方法将实例化ClassPredictionError可视化程序并将其适合于训练数据，然后将其在可选提供的测试数据（或未提供的训练数据）上评分。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from yellowbrick.datasets import load_concrete\r\n",
    "from yellowbrick.regressor import cooks_distance\r\n",
    "\r\n",
    "# Load the regression dataset\r\n",
    "X, y = load_concrete()\r\n",
    "\r\n",
    "# Instantiate and fit the visualizer\r\n",
    "cooks_distance(\r\n",
    "    X, y,\r\n",
    "    draw_threshold=True,\r\n",
    "    linefmt=\"C0-\", markerfmt=\",\"\r\n",
    ");"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "# 5 参考\n",
    "[https://www.scikit-yb.org/en/latest/api/regressor/residuals.html](https://www.scikit-yb.org/en/latest/api/regressor/residuals.html)\n",
    "\n",
    "[https://www.scikit-yb.org/en/latest/api/regressor/peplot.html](https://www.scikit-yb.org/en/latest/api/regressor/peplot.html)\n",
    "\n",
    "[https://www.scikit-yb.org/en/latest/api/regressor/alphas.html](https://www.scikit-yb.org/en/latest/api/regressor/alphas.html)\n",
    "\n",
    "[https://www.scikit-yb.org/en/latest/api/regressor/influence.html](https://www.scikit-yb.org/en/latest/api/regressor/influence.html)"
   ]
  }
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